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Control Systems Engineering - Science topic

Control engineering or control systems engineering is the engineering discipline that applies control theory to design systems with desired behaviors.
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会议征稿:第四届计算机、物联网与控制工程国际学术会议(CITCE 2024)
Call for papers: 2024 4th International Conference on Computer, Internet of Things and Control Engineering (CITCE 2024) will be held on November 1-3, 2024 in Wuhan, China as a hybrid meeting.
Conference website(English):https://ais.cn/u/IJfQVv
重要信息
大会官网(投稿网址):https://ais.cn/u/IJfQVv
大会时间:2024年11月1-3日
大会地点:中国-武汉
收录类型:EI Compendex,Scopus
会议详情
第四届计算机、物联网与控制工程国际学术会议(CITCE 2024)将于2024年11月1-3日在中国-武汉召开。CITCE 2024将围绕计算机、物联网与控制工程的最新研究领域,为来自国内外高等院校、科学研究所、企事业单位的专家、教授、学者、工程师等提供一个分享专业经验、扩大专业网络、展示研究成果的国际平台,以期推动该领域理论、技术在高校和企业的发展和应用,也为参会者建立业务或研究上的联系以及寻找未来事业上的全球合作伙伴。大会诚邀国内外高校、科研机构专家、学者,企业界人士及其他相关人员参会交流。
征稿主题
1. 计算机科学:演算法、图像处理、计算机视觉、机器学习、智能数据分析与数据挖掘、数学和计算机建模、人工智能、神经网络、系统安全、机器人与自动化、信息系统、高性能计算、网路通讯、人机交互、电脑建模等;
2. 物联网:人工智能技术与应用、CPS技术与智能信息系统、物联网环境中的多网资源共享、物联网技术体系架构 、物联网中的云计算与大数据、边缘智能与区块链、智慧城市、物联网可穿戴设备 、智能家居、物联网与传感器技术等;
3. 控制工程:系统和自动化、电气系统、过程控制、工业控制技术、计算机科学与工程、电子工程学、软件工程、控制技术、传感器网络、移动互联网、无线网络和系统、计算机控制系统、自适应和最优控制、智能控制、电气自动化、智能控制和智能系统、智能管理和决策、分布式控制、驱动电机和控制技术、动力电池管理和维护技术、微传感器和执行器、移动机器人等
**其它相关主题均可
会议出版
会议投稿经过2-3位组委会专家严格审核后,最终所录用的论文将被ACM ICPS (ACM International Conference Proceeding Series)(ISBN:979-8-4007-1184-8) 出版论文集,并提交至ACM Digital library,EI Compendex, Scopus检索。目前该会议论文检索非常稳定。
参会方式
1、作者参会:一篇录用文章允许一名作者免费参会;
2、参会类型
(1)口头汇报:10-15分钟的全英PPT演讲;
*开放给所有投稿作者与自费参会人员;针对论文或者论文里面的研究做一个10-15min的英文汇报,需要自备PPT,无模板要求,会前根据会议邮件通知进行提交,详情联系会议秘书。
(2)海报展示:自制电子版海报,会议安排展示;
*开放给所有投稿作者与自费参会人员;格式:全英-A1尺寸-竖版,需自制;制作后提交海报图片至会议邮箱IC_CITCE@163.com,主题及海报命名格式为:海报展示+姓名+订单号。
(3)仅参会:非投稿作者,现场听众参会。
*仅开放给自费参会人员
(4)投稿参会链接:https://ais.cn/u/IJfQVv
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For more details about the conference, please visit the official website of the conference: https://ais.cn/u/IJfQVv
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会议征稿:第七届机械、控制与计算机工程国际学术会议(ICMCCE2024)
Call for papers: IEEE 2024 7th International Conference on Mechanical, Control and Computer Engineering (ICMCCE 2024), organized by Chaohu University and Shenyang Ligong University will be held in Hangzhou during October 25 to 27, 2024.
Conference website(English):https://ais.cn/u/IrMvmq
重要信息
大会官网(投稿网址):https://ais.cn/u/IrMvmq
大会时间:2024年10月25-27日
大会地点:中国杭州
收录类型:EI Compendex,Scopus
主办单位:巢湖学院
会议详情
第七届机械、控制与计算机工程国际学术会议定于2024年10月25日至27日在中国杭州召开。本届会议由巢湖学院主办,主要围绕“机械”、“控制”与“计算机工程”等研究领域展开讨论。旨在为机械、控制与计算机工程方面的专家学者及企业发展人提供一个分享研究成果、讨论存在的问题与挑战、探索前沿科技的国际性合作交流平台。欢迎海内外学者投稿和参会。
会议征稿主题(包括但不限于)
1、机械工程
2、自动化及控制工程
3、计算机工程
4、电子和通信技术
更多相关主题请查看官网
论文出版
本次会议投稿论文都须经过2-3位组委会专家审稿,最终录用的论文将提交出版,见刊后提交至 EI Compendex、Scopus检索,目前该出版社EI检索非常稳定。往届会议已被EI检索!
投稿参会方式
所有参会人员均可申请报告或海报展示,可开具证明
1、作者参会:录用文章允许一位作者免费参会
① 申请听众参会,无需准备报告或海报;
② 申请口头报告,时间为15分钟,PPT&报告语言为英文;
③ 申请海报展示,A1尺寸,彩色打印(自行打印);
2、主讲嘉宾:申请主题演讲,由组委会审核;
3、听众参会:只参会听讲不投稿,也可申请口头报告或海报展示;
4、报名参会:https://ais.cn/u/IrMvmq
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interested
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I have a system with 3 input and single output. In system Identification toolbox of MATLAB, how i put the 3 input data sets for estimating the system models  simultaneously?
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here
just note you need to import both two inouts from ''processes>select channles'' then highlight both inputs so they can be active before using ''estimate''.
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2024 IEEE 6th International Conference on Internet of Things, Automation and Artificial Intelligence(IoTAAI 2024) will be held in Guangzhou, China from July 26 to 28, 2024.
Conference Webise: https://ais.cn/u/InumA3
The conference aims to provide a large platform for researchers in the field of modern machinery manufacturing and materials engineering to communicate and provide the participants with the most cutting-edge scientific and technological information. The conference invites experts and scholars from universities and research institutions, business people and other related personnel from home and abroad to attend and exchange ideas.
---Call For Papers---
The topics of interest for submission include, but are not limited to:
1. Internet of Things
IoT Electronics
IoT Enabling Technologies
IoT Networks
IoT Applications
IoT Architecture
......
2. Automation
Electrical Automation
Circuits and Systems
Control Engineering
Robotics and Automation Systems
Automatic control and Information Technology
......
3. Artificial Intelligence
Intelligent Systems
Intelligent Optimized Design
Virtual Manufacturing and Network Manufacturing
System Optimization
......
All accepted full papers will be published and submitted for inclusion into IEEE Xplore subject to meeting IEEE Xplore's scope and quality requirements, and also submitted to EI Compendex and Scopus for indexing.
Important Dates:
Full Paper Submission Date: May 11, 2024
Registration Deadline: July 24, 2024
Final Paper Submission Date: July 22, 2024
Conference Dates: July 26-28, 2024
For More Details please visit:
Invitation code: AISCONF
*Using the invitation code on submission system/registration can get priority review and feedback
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Thanks
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How can I implant ANFIS as a controller in MATLAB/SIMULINK simulation for sit to stand movement supported with functional electrical stimulation in paraplegics. I think it will be inverse dynamic model and I should use model base controller
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Suppose that you want to apply fuzzy inference to a system for which you already have a collection of input/output data that you would like to use for modeling, model-following, or some similar scenario. Also, assume that you do not necessarily have a predetermined model structure based on the characteristics of variables in your system. In some modeling situations, discerning membership functions parameters by looking at data can be difficult or impossible. In these cases, rather than choosing the parameters associated with a given membership function arbitrarily, you can tailor the membership function parameters to the input/output data. Using Fuzzy Logic Toolbox™ software, you can tune Sugeno fuzzy inference systems using neuro-adaptive learning techniques similar to those used for training neural networks
Regards,
Shafagat
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Thank
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Yes, you can use a Triggered Subsystem in MATLAB Simulink to implement a low-pass filter on a PWM signal. The Triggered Subsystem allows you to execute a block of Simulink model when a specific condition is met, which in this case would be the PWM signal exceeding a certain frequency threshold.
A high-level overview of how you can design this technique in MATLAB Simulink is:
1 - Generate the PWM signal: Start by generating the PWM signal that you want to filter. You can use appropriate blocks or functions in Simulink to generate the PWM waveform based on your requirements.
2 - Measure the frequency: Use a frequency measurement block or algorithm to measure the frequency of the PWM signal. This could be achieved using techniques such as zero-crossing detection or FFT analysis.
3 - Compare with the threshold: Compare the measured frequency with the desired frequency threshold (20 kHz in your case). You can use a Comparison block or an if-else condition to make this comparison.
4 - Triggered Subsystem: Inside the Triggered Subsystem block, design the low-pass filter. You can use standard Simulink blocks, such as a Discrete-Time Integrator and a Discrete-Time Transfer Function block, to implement a simple low-pass filter. Adjust the filter parameters based on your desired cutoff frequency.
5 - Connect the subsystem: Connect the output of the Triggered Subsystem to the appropriate output in your Simulink model, so that the filtered PWM signal can be utilized for further processing or analysis.
6 - Configure the Trigger: Set up the trigger condition for the Triggered Subsystem. In this case, the trigger condition would be the comparison result from step 3.
7 - Simulate and analyze: Simulate the Simulink model and observe the filtered PWM output. Verify that the frequencies above 20 kHz are effectively attenuated while the frequencies below 20 kHz are passed through.
It's important to note that the specific details of your implementation may vary depending on your PWM signal source, sampling rate, desired filter characteristics, and any other additional requirements. Experimentation and fine-tuning may be necessary to achieve the desired filtering behavior.
By utilizing the Triggered Subsystem and appropriate filter blocks, you can implement a low-pass filter on a PWM signal in MATLAB Simulink, removing high frequencies above the specified threshold while allowing frequencies below it to pass through.
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Background:
In control theory we often develop new methods for analysis or controller/observer/filter design and usually evaluate them with numerical simulations. In many papers only a few selected examples are considered.
I think it would be desirable, if there was a catalogue of potential example systems which contains a variety of system models from one could select those which are suitable for a specific use case. A colleague and I are working on such a catalogue (see https://ackrep.org for more information).
After establishing the framework, a basic ontology ("Ontology of Control Systems Engineering") and some preliminary examples (e.g. cart pole system, Brockett integrator, some PDEs and DAEs), we now look for more content. Another colleague recommended http://www.compleib.de/ which contains > 100 linear state space systems.
I am also aware of some other small collections of nonlinear/mechanical systems (available only as PDF file) such as :
Differential Flatness of Mechanical Control Systems: A Catalog of Prototype Systems, 1995 Murray, Rathinam, Sluis
Question:
Are you aware of other catalogues or collections of dynamical systems? Preferably, the equations (and potential metadata) are available in a machine actionable format, but this is optional.
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With respect to electric motors / drives, we have collected a database of 500+ different parameter sets describing the first principle dynamics of permanent magnet synchronous motors which are publicly available here: https://github.com/upb-lea/meta_RL_PMSM
The parameter set originates from real-world, industry grade motor series. In addition, we offer an upsampling scheme to produce additional ‘artificial’ parameter sets if desired.
For simulation, the parameter sets can be loaded and processed using the following framework: https://github.com/upb-lea/gym-electric-motor
Although this model set only describes one specific kind of ODE structure, the dynamics of the covered motors (from few watts to hundreds of kilowatts) varies strongly.
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I hope this message finds you'll well. My name is Onyero Walter Ofuzim. I am reaching out to express my interest in collaborating in the field of Electrical/Electronic Engineering mainly in Control Systems Engineering, Dynamic Networks, Machine Learning, IoT, and/or Robotics.
I am deeply passionate about these areas and have been actively involved in research and projects related to them. I firmly believe that collaborating with others in this field will not only increase my chances of getting into a foreign-funded Masters or Ph.D. program, which is my ultimate goal but also help drive innovation and advancements in the field.
I am eager to share my ideas and knowledge and learn from others to contribute to the growth and development of these cutting-edge technologies. I am confident that my skills and experience will be a valuable asset to any team, and I look forward to the opportunity to work with anyone who will be nice to have me.
Thank you for considering my request for collaboration. I look forward to hearing about a possible invitation.
Feel free to explore my profile as I am optimizing it to make my chances high.
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I admitted as an undergraduate to multiple universities in Arizona and Colorado! I have been actively looking for admission to the university to continuously prepare me as an investigator/innovation scientist in mineral exploration by building my foundational knowledge in metallurgy, chemistry, control systems engineering, geochemistry, geophysics, etc. These might be included in my coursework. My focus may be on "control system engineering" compared to "geoscience," as I want to spend my effort investigating sensor innovation using metallurgy, geophysics, chemistry, etc. for mineral exploration. Precisely, investigative research will be on creating "detection technology for purposing of Mining exploration and extraction" So, I'm confused with two queries: 1. Which university would be the best option based on my research interests? 2. Which major and region for internship/ real time research job corresponds to what I'm actually looking for?
Hope you already understand I’ve applied many universities with getting rejection that didn’t also find exact research team yet I’m looking. Thank you so much.
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Dear Saifur Rahman Khan and Al,
lI wish you Happy New Year: success in your spiritual achievement, good health and prosperity for it!
I found the next on the facbook (https://www.facebook.com/USGSVolcanoes):
'A volcanologist is a person who studies volcanoes, but there are many different specialties within the field of volcanology. Which interests you and what steps should you take to achieve your goal? Find out more in #VolcanoWatch.
Earthquakes are one primary tool used to study volcanoes. A volcano seismologist studies the earthquakes that are generated as magma moves through Earth’s crust.
A volcano geodesist studies the deformation, or change in shape, of a volcano caused by the movement of magma and gases beneath the surface. Many features of volcanoes can be studied from space, as well, using satellite sensors. Tools like these provide clues about the state of the volcano.
Geologists and geochemists study the composition of lavas and gases to understand the source and style of the eruption. Measuring gas emissions is especially important, as the vog (volcanic air pollution) caused by toxic volcanic gases can contribute to breathing problems, acid rain, and agricultural problems downwind, especially during long-lived eruptions.
If you are interested in becoming a volcanologist, you’ll need to work toward a bachelor’s degree, preferably in a STEM field (Science, Technology, Engineering, and Math). Volcanologists frequently pursue degrees in geology, chemistry, physics, and/or mathematics, but that is not always the case. Oceanography, computer science, engineering, environmental science are all potential pathways, and the list goes on. Explore different fields to find what interests you most.
After achieving a bachelor’s degree, consider options for advanced degrees like a Masters or Doctorate. Many advanced degree programs in the sciences are funded, meaning tuition may be waived, and you might get a stipend for doing the work. Basically, you get paid instead of having to pay for school, and you gain valuable work experience at the same time.
You might consider working for the USGS or other agencies and companies. You have seen many photos of HVO scientists working during the eruptions of Mauna Loa and Kīlauea. The National Park Service also offers a variety of positions for people with either bachelor’s or advanced degrees, such as park geologists, archaeologists, botanists, guides, interpretive rangers, and law enforcement rangers. Science writing and journalism are also excellent ways to explore the excitement of volcanology, natural disasters, and cutting-edge science, while encouraging those passions in others. Similarly, eco- and geo-tourism are great ways to get close to the action and work outdoors, while also meeting, educating, and inspiring people from all over the world. Careers in emergency management will have you helping people stay informed during crises.
Check out usajobs.gov for positions within the federal government. There is even a special section for students and recent grads.
Volcano Activity Updates
#MaunaLoa is not erupting. Webcam imagery shows weak, residual incandescence intermittently in the inactive Northeast Rift Zone fissure 3 lava flow at night. Seismicity remains low and ground deformation rates have decreased. Sulfur dioxide (SO2) emission rates are at background levels. For Mauna Loa monitoring data, see: https://www.usgs.gov/volcanoes/mauna-loa/monitoring-data.
#Kilauea is not erupting. Lava supply to the Halemaʻumaʻu lava lake in Hawai‘i Volcanoes National Park ceased on December 9. Sulfur dioxide emission rates have decreased to near pre-eruption background levels and were last measured at approximately 200 tonnes per day (t/d) on December 14. Seismicity is elevated but stable, with few earthquakes. Over the past week, summit tiltmeters recorded several deflation-inflation (DI) events. For Kīlauea monitoring data, see https://www.usgs.gov/.../past-week-monitoring-data-kilauea.
There were three earthquakes with 3 or more felt reports in the Hawaiian Islands during the past week: a M3.3 earthquake 14 km (8 mi) S of Fern Forest at 7 km (4 mi) depth on Dec. 27 at 4:33 a.m. HST, a M3.4 earthquake 7 km (4 mi) WSW of Volcano at 2 km (1 mi) depth on Dec. 24 at 8:31 p.m. HST, and a M2.5 earthquake 1 km (0 mi) S of Mountain View at 11 km (7 mi) depth on Dec. 24 at 9:57 a.m. HST.
In the photo, an HVO technician adjusts a volcanic gas analysis instrument that was specifically designed for this Unoccupied Aircraft System (UAS) unit, which carries three one-liter analysis bags. The instrument transmits gas concentration information in real-time during the flight at Kīlauea summit. USGS has special use permits from the National Park Service to conduct official UAS missions as part of HVO's mission to monitor active volcanoes in Hawaii, assess their hazards, issue warnings, and advance scientific understanding to reduce impacts of volcanic eruptions. Launching, landing, or operating an unoccupied aircraft from or on lands and waters administered by the National Park Service within the boundaries of Hawai‘i Volcanoes National Park is prohibited under 36 CFR § 1.5 - Closures and public use limits.
USGS image taken January 14, 2022 by M. Warren.
#USGS #HVO #HawaiianVolcanoObservatory'
Maybe it can help you!
Regards,
Laszlo
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With this question, I want to know that proper systems exist? or they are just theoretical systems?
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Hi Marco, you have already received good answers, all complementary, check Silvano Meroni and Yew-Chung Chak 's responses.
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In his name is the judge
Hi everyone
In order to use controller for structure with absorber, have to connect matlab and opensees in real time :
it means in each loop in opensees data must send to matlab and then matlab do some prossess with controller like fuzzy then send back data to opensees
Relying on researching and consulting the only way is use hybrid simulation (like openfresco),
do you have any other idea or way to connect these two programs without using openfresco?
Translation results
star_border
Consult
Wish you best.
Take refuge in the right.
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Use TCP/IP communication.
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I already saw some examples of GA (genetic algorithm) applications to tune PID parameters, but I (until now) don't know a way to define the bounds. The bounds are always presented in manuscripts, but they appear without great explanations. I suspect that they are obtained in empirical methods.
Could Anyone recommend me research?
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Dear Italo,
In general, the bounds selection is made empirically because the "suitable range" of a PID controller is problem-dependent. The way I use to select the bounds is: 1. I tune a PID controller that produces a stable response to the closed-loop system. Then, 2. I choose a range around this "nominal" value large enough such that the GA has still some degree of freedom to search in the optimization space. Finally, 3. if the GA converges, I start decreasing/increasing this range till I got a more or less good behavior of the GA, i.e., the GA doesn't stick in a sub-optimal minimum or so.
If you want to use a more rigorous approach, I would suggest computing the set of all stabilizing PID controllers for the particular system. Then, I would establish the bounds for the GA search space to be the this computed set. In that way, you would search for the optimal controller only within those producing a stable closed-loop response.
Best,
Jorge
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How long does it take to a journal indexed in the "Emerging Sources Citation Index" get an Impact Factor? What is the future of journals indexed in Emerging Sources Citation Index?
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According to Web of Science, ESCI Journal can be included in Science Citation Index (SCI), Social Science Citation Index (SSCI), or Arts and Humanities Citation Index (AHCI), if they meet "Impact Criteria".
Accordingly, journals are included in Web of Science Core Collection (SCI, SSCI, AHCI, and ESCI) if they meet 2 criteria, namely; 1) Quality 2) Impact. The "Quality criteria" comprises 24 sub-criterion, while the "Impact criterion" consist of 4 sub-criteria.
Hence, any journal captured in ESCI have already meet the quality criteria , therefore the quality criteria is the only requirement for journal to be considered in ESCI. Similarly, any journal on ESCI must wait to meet the "Impact Criteria", which can take time, and may be impossible to be predicted. This is because the Impact Criteria is evaluated according to the number of citations the journal is receiving, the performance of authors who published in the journal before, and the number of cross-references between journals in web of science, etc. Waheed Ur Rehman .
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As IEC 61131-3 standard for PLC programming languages defines a few of them, it will be useful to learn what our colleagues apply for PLC programming.
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The ladder
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Does anyone know if I can connect the attached DAQ (CASSY type) to MATLAB real time simulink for controlling purposes?
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It depends on your sample frequency, which is limited for performance of DAQ. another issue should be concerned is the number analog of a processing control system. the quality of data will be bad or real-time data might be good if you collect as much data in process as possible.
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Hi
How can i correct this error?? I think it's about matrix dimensions for port e.
Error in default port dimensions function of S-function 'FeedbackLinearization/Controller'. This function does not fully set the dimensions of output port 2
I'm running a simulation based on feedback linearization control method that comes from a paper attached below.
the model is also attached.
Anyone help me, helps a poor student. (if it makes sense lol)
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Hi,
file name "sfun_ abcaaaaa.c" is not available in the folder mentioned.
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Assuming that no motion in the normal direction, how would you propose a system of hardware and interconnection as well as the control strategy that will drive the system?
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Sounds analogous to an inverted pendulum. Here is one way to construct something with closely similar dynamics. Take a knee (90° angle) connector for sewage pipe, cut it nicely and mount it on a toy car such that the knee is pointing straight upwards. Place a small ball (i.e. from a roll-on bottle) on top of the knee and try to keep it there stably by moving the toy car back, forth, and sideways (hard to do manually without automated feedback control loop). I guess many feedback control schemes would keep the ball at the top of this curve subject to micromotion.
Aside: If the knee was facing down, mounted on a motor, and the ball is placed inside the 90° curve while the motor is rotated at some angular frequency, the resulting dynamics would resemble Mathieu equations whose stability analysis could be checked from Floquet theory. Incidentally, these are the same dynamics exhibited by a single ion trapped in a linear Paul trap.
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Suppose we have a lipschitz nonlinear system with a disturbance input. The disturbance is of decaying exponential like nature with an upper bound known. 
System: x_dot = f(x) + g(x)u(t) + d(t)
where, x:state; u(t): control input; d(t): Disturbance input
How can we design nonlinear observer for such system?
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Disturbance is sometimes helpful while dealing with multicollinearity. Also helpful may be keeping the number of degrees of freedom minimum.
Maybe you can alernatively consider the recursive least squares algorithm (RLS). RLS is the recursive application of the well-known least squares (LS) regression algorithm, so that each new data point is taken in account to modify (correct) a previous estimate of the parameters from some linear (or linearized) correlation thought to model the observed system. The method allows for the dynamical application of LS to time series acquired in real-time. As with LS, there may be several correlation equations with the corresponding set of dependent (observed) variables. For the recursive least squares algorithm with forgetting factor (RLS-FF), adquired data is weighted according to its age, with increased weight given to the most recent data.
Years ago, while investigating adaptive control and energetic optimization of aerobic fermenters, I have applied the RLS-FF algorithm to estimate the parameters from the KLa correlation, used to predict the O2 gas-liquid mass-transfer, hence giving increased weight to most recent data. Estimates were improved by imposing sinusoidal disturbance to air flow and agitation speed (manipulated variables). The power dissipated by agitation was accessed by a torque meter (pilot plant). The proposed (adaptive) control algorithm compared favourably with PID. Simulations assessed the effect of numerically generated white Gaussian noise (2-sigma truncated) and of first order delay. This investigation was reported at (MSc Thesis):
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Hi!
I have started working on a project "floating sensor networks (FSN) for continuous water quality monitoring". For which I need simulator to measure Like, pH, Turbidity, Salinity, Temperature, DO, EC, etc. Rather than going with real time deployment of FSN for measuring water quality sensors.
Objectives of the Project:
A. Water Quality Measurement
B. Reliable Data Transform
C. Congestion Control
D. Deployment Strategy
E. Energy Harvesting
All objectives should be carried out simulation based. Kindly suggest whether this work will done via simulation design (either partially or whole) 
Thanks in Advance.
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Dear Sarang, did you find any suitable simulation software? We also need it for a small project we are working on
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Hello everyone,
I'm looking for some short courses (not online) in the field of CE (more interested in Automotive control) in Europe.
My field of interests are,
- Robotic Control Systems
- Vehicular Dynamics Control
- Motion Control
- Data-Driven Control
- Optimal Control
- System Identification
- Reinforcement Learning Control Design.
I can participate by Self-Fund but I will be happier if there will be a scholarship or something,
please help me in this area if you have any experience,
Thanks a lot for reading,
Yours cordially,
A. M.
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We can avoid dq transformation by using PR controller. Why don't we use PR controller in industry? Why do we prefer PI controller?
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Hello, if possible, please explain more about this. Thank you
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it means the oil pump to be sometimes able to turn off during the driving cycle, and if it is possible, how efficient would it be? (more particularly in heavy vehicles like a bus).
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It depends upon the size of the accumulator, and the flowrate required. If you calculate the flowrate required for the PAS pump you could work out the accumulator volume required. See link below for typical (but a little old) energy consumption info.
However, many modern vehicles are moving to electric PAS systems, so the traditional hydraulic system may not be required in future.
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I am designing a flight controller for a quadrotor.
At first I am designing a nested/cascaded controller consisting of only proportional controllers Kp . Now, if i tune the rate controller for 10 rad/s cross-over frequency, what should be the cross-over frequency for the angle, velocity and then the position loops. Also, what else do i need to know while designing a flight controller for practical implementation purposes?
Secondly, How do we implement a own flight controller such as observer based via arducopter?
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Thanks alot for your time! These links are really helpful!
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I am trying to discretize a continuous time state space model using the following code
s=tf('s');
G=1/(Iyy*(s^2))
Gs=ss(G)
Gd=c2d(Gs,0.01,'zoh');
Now, when i use this discretized model 'Discrete State-space Model' in simulink, my close loop system goes unstable. Same is happening with observer, like discretized observer is making close loop system unstable. Can someone help me here?
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Your system is basicly a double integrator, so a borderline stable system. If you look at your phase value of the bode plot for the continious system (bode(G)), you will see that it has a phase of -180° over all frequencies. Since any kind of delay causes the phase of a system to drop, if you introduce an arbitrarily small amount of delay on your continious tf G, and use the command "margin(G)", you will find that your system will always have a negative phase margin. And since discretizing will always introduce delay into your system, closing the loop on it will automatically destabalize it. You can use 'tustin' as you discretizing method, which essentialy uses trapezoidal integration, a more stable integration algorithm, and simulink should probably get your discrete system stable this way.
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Consider a system with relative degree two with respect to a chosen sliding output function s. If twisting controller is applied for control, what are the expected drawbacks in control performance and steady state behaviour? You may consider that $s$ and $\dot{s}$ is available.
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1. Historically twisting have been designed to substitute a discontinuous controller with Lipschitz continuous one keeping the finite-time theretically exact convergence to the sliding output for the systems with relative degree one affected by Lipschitz perturbaitons(see Levant A. IJC, 1993 https://www.tau.ac.il/~levant/slorder93.pdf).
The only adavantage of the twisting controller is that if this algorithm is applied for the systems with relative degree two it ensures theoretically exact finite-time convergence of the sliding output and its derivative to zero in finite-time.
But from the viewpoint of chattering the twiating controller is the worst one because his gains are at least twice bigger, than the upper bound of uncertainties.
Moreover, the amplitude of chattering produced by twisting controller is bigger than the amplitude of chattering produced by relay controller with a linear sliding surface see attached file, table 3
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PID controller is reportedly widely built and used in control systems engineering for industrial applications. The PID-controller has a transfer function as: (Kd*s^2+Kp*s+Ki)/s.
Therefore, it seems such a transfer function box, could be built in terms of an electronic circuit component.
Meanwhile, the order of an observer-based controller is higher than a PID-controller, as for example you see in the snap-shot from Ogata control engineering book, attached. Since Ogata is a practical engineering text-book, therefore I guess such an observer-based controller could be practically built as an electronic circuit and then embedded as a controller.
Moreover, we usually build transfer function blocks, simply in Matlab Simulink. But is it possible, practical, simple, and convenient to build such blocks as an integrated electronic element in a circuit, while they are of high order?
My main question:
There is a controller, with a transfer-function:
H_controller(s)=N(s)/D(s),
Where:
N(s)=b0*s^m+b1*s^(m-1)+b2*s^(m-2)+…+bm,
And:
D(s)=a0*s^n+a1*s^(n-1)+a2*s^(n-2)+…+an.
Moreover, m=10, n=10, or, n=11.
The digested question:
Is it possible, and practical to design an electronic circuitry for a box, with the transfer function: H_box=H_controller(s)=N(s)/D(s)?
Warning: I have no experience to build a real electronic circuitry, and my question is only the possibility and practicality of designing a circuit for such a transfer function box. Do not mind about the performance of the controller or any other stability concern with regard to that. Only the possibility and practicality of designing an electronic box which has an equivalent transfer function: H_box=H_controller(s)=N(s)/D(s).
The box is in feed-forward path.
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The transfer function H(s)= N(s)/D(s)
has the form of filter characteristics.
Such general transfer characteristics has zeros and poles.
The filter which contains zeros and poles are elliptic filters.
Such filters can be implemented by using op amps+ discrete RC elements
They can be built completely integrated using switched capacitor filters
They can be also implemented by using gm-C filters.
For such filter design using active filters please follow the reference: https://www.sciencedirect.com/book/9780750675475/analog-and-digital-filter-design
Bestwishes
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I want to know that we have a real system with fractional order state space model
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Dear Professor Sabatier
First, I'd like to thank you so for asking these kind of challenging questions. These kinds of questions are very important for advancing this field. As you said, our life is full of doubts. Now this question arise that: How can we trust to different integer differential models? The only sin of fractional derivative is that it has been introduced after integer derivative. Why should we accept that the first derivative (u') denotes the velocity? Why another fractional derivative (such u^{0999}) is not?
As we can check in many considerable works, fractional derivatives modify many old results in integer derivatives. As you said, you often use fractional models to build and implement very physical and useful systems (eg: battery state observers, hydrogen generator, ...). We need a comparison in study of these different natural phenomena and so a standard basic theory for the comparison which is usually integer derivative models while we can doubt it. I fee that we could improve our initial mental attitude. Again, I appreciate you.
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I'm studying digital control by myself, and I would like to know if has available on the internet the solutions manual of "Digital Control of Dynamic System 3rd edition"?
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For example, the first order Laplacian measures the difference between the local and average values of a quantity in an infinitesimal neighborhood of the point in question. So, for a flexible string, the acceleration is proportional to the Laplacian (wave equation).
For plates, the acceleration is proportional to the double Laplacian. Also, the double Laplacian occurs in the modification of the wave equation for a stiff string. Therefore, what is the double Laplacian a measure of? Thanks.
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We have:
Applications of Double Laplace Transform to Boundary Value Problems DOI: 10.9790/5728-0925760
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I only have acces to historical data recorded over the course of a few years. However the data is of a closedloop proces that has already been tuned with PID. The values of P, I and D are known.
How can I determine the openloop transferfunction usign only this data?
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Is it theoretically possible, that after discretization by using Talyor Series Expansion, a non-observable nonlinear system will became an observable?
It was proved, that used continuous model of PMSM is non-observable (see attached). I want to know, if resulting discrete system is observable or not. Any comment appreciated. Thanks.
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the dc-dc converters has two transfer functions , control to output and line to output TF. which one is used when design a controller? and which one is used to test step response?
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I agree with Aparna Sathya Murthy
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I'm a beginner in control engineer, what books or websites you could recommend?
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T. Bauer, J.T. Betts, W. Hallman, W.P. Huffman, K. Zondervan, Solving the optimal control problem using a nonlinear programming technique, Parts I and II, 1984.
A.E. Bryson Jr.Optimal control – 1950 to 1985
IEEE Control Systems (1996),
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Suppose a six degree of freedom simulation of an aircraft, which some aerodynamic parameters (e.g: stability derivatives), mass configuration (e.g center of mass) and etc, are randomly choose within known bounds. From the Monte Carlo sample those simulations are split in two groups: with instability (any time during the simulation) and without instability during the flight.
My question is, How could I find the more important combination of random parameters the caused the instability in flight?
I have already done a sensitivity analysis, so I have an idea how each one influence individually. What I really one to find is how the combination of parameter is causing the instability.
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For more details, we have:
Monte Carlo Simulation of Real Dynamic Systems :
Best regards
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Hi every one,
here I have a problem in MATLAB, when I want to solve the following equation, relative to PI in the photo, or tau in the code, MATLAB will send me this error: Warning: Unable to find explicit solution. For options, see help.
I attached the question and the code below (in code, I rewrite pi in the photo with tau).
If you have any idea to solve this problem, analytically or numerically, I will be happy to hear it out.
NOTE:
> PI_0.1(X,t) = tau
> X = [x(t),y(t),psi(t)]^T;
** PROBLEM: Find tau in terms of X and t in which solve the mentioned equation.
Thanks in advance,
Arash.
code:
______________________________________
______________________________________
clc;clear;
syms x y psi tau t
c1 = 1;c2 = 1.5;lambda = 0.1;
x_r(tau) = 0.8486*tau - 0.6949;
y_r(tau) = 5.866*sin(0.1257*tau + pi);
psi_r(tau) = 0.7958*sin(0.1257*tau - pi/2);
x_r_dot = 0.8486;
y_r_dot(tau) = 0.7374*cos(0.1257*tau + pi);
psi_r_dot(tau) = 0.1*cos(0.1257*tau - pi/2);
phrase1 = c1/2*(cos(psi)*(x - x_r) + sin(psi)*(y - y_r))*(cos(psi)*x_r_dot + sin(psi)*y_r_dot);
phrase2 = c1/2*(-sin(psi)*(x - x_r) + cos(psi)*(y - y_r))*(-sin(psi)*x_r_dot+cos(psi)*y_r_dot);
phrase3 = 0.5*(psi - psi_r)*psi_r_dot;
eq = -2*(1-lambda)^2*(phrase1 + phrase2 + phrase3) - 2*lambda^2*(t - tau)
sol = solve(eq == 0 , tau , 'IgnoreAnalyticConstraints',1)
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Pass x, instead of tau, as rightly pointed out by Saeb AmirAhmadi Chomachar
syms x y psi tau t
c1 = 1;c2 = 1.5;lambda = 0.1;
x_r(tau) = 0.8486*tau - 0.6949;
y_r(tau) = 5.866*sin(0.1257*tau + pi);
psi_r(tau) = 0.7958*sin(0.1257*tau - pi/2);
x_r_dot = 0.8486;
y_r_dot(tau) = 0.7374*cos(0.1257*tau + pi);
psi_r_dot(tau) = 0.1*cos(0.1257*tau - pi/2);
phrase1 = c1/2*(cos(psi)*(x - x_r) + sin(psi)*(y - y_r))*(cos(psi)*x_r_dot + sin(psi)*y_r_dot);
phrase2 = c1/2*(-sin(psi)*(x - x_r) + cos(psi)*(y - y_r))*(-sin(psi)*x_r_dot+cos(psi)*y_r_dot);
phrase3 = 0.5*(psi - psi_r)*psi_r_dot;
eq = -2*(1-lambda)^2*(phrase1 + phrase2 + phrase3) - 2*lambda^2*(t - tau);
eqn = rewrite(eq,'log');
sol = solve(eqn == 0 , x , 'IgnoreAnalyticConstraints',1);
pretty(sol)
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I want to know the exact definition of these four tests and I am wondering which of them could work in real time?
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HIL or 'hardware-in-the-loop' testing is by its very nature a resource-hungry solution to testing, requiring multi-skilled teams able to set up and configure both the execution platform and the I/Os as well as the modelling environment.
Once your model is verified (i.e., MIL in the previous step is successful), the next stage is Software-in-Loop(SIL), where you generate code only from the Controller model and replace the Controller block with this code.
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I have the nonlinear systems of Khalil, however some definitions are no so clear, is there a newer book with Matlab examples
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For Video tutorials , we have:
Introduction | Nonlinear Control Systems: https://www.youtube.com/watch?v=Xgnwn0G9qoo
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Hello everybody
Despite a few TMD cost models available in the literature, I am searching for more accurate initial and lifetime cost models of translational TMDs for Life Cycle Cost Analysis (LCCA) of TMD-equipped structures.
In fact, the provided cost model affiliated with one of the companies designs and manufactures transitional TMD (such as LeMessurier CO.), which this model consists TMD initial cost (construction and installation of the TMD) and TMD damage cost (maintenance and repair losses of TMD before structural collapse)
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The effectiveness of tuned mass dampers (TMDs) in reducing the seismic response of civil structures is still a debated issue. The few studies regarding TMDs on inelastic structures indicate that they would perform well under moderate earthquake loading, when the structure remains linear or weakly nonlinear, while tending to fail under severe ground shaking, when the structure experiences strong nonlinearities. TMD seismic efficiency should be therefore rationally assessed by considering to which extent moderate and severe earthquakes respectively contribute to the expected cost of damages and losses over the lifespan of the structure.
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I design feedback close loop system with a robust static feedback controller using Hinf approach where control low is u(t)=Kx(t). What is the good method to show robustness for this type of system? What plots we can make to show robustness for designed system?
Regards
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Dear community,
I am trying to build a model of a Furuta pendulum in Simulink/Simscape. Unfortunately, when I try to linearize my model with the integrated Model Linearizer, I get an unexpected result. The evaluation of the linearized system shows, that it is only poorly controllable, although a classic Furuta pendulum should be fully controllable according to literature. Therefore I assume, that there must be something wrong with my model or the way I linearized it but I can´t figure out what it is.... I´d highly appreciate any help on that, as this is bothing me for quite some time now. The model is attached to this post. Furthermore I have attached a screenshot of the linearized system.
My controllability matrix (ctrb(A,B)) then looks like this with rank = 1, which I believe can´t be right...
Controllability matrix =
1.0e+26 *
0 0.0000 0.0000 -0.0000 0.0000
0.0000 0.0000 -0.0000 0.0000 -0.0007
0 0.0000 0.0000 -0.0000 0.0000
0.0000 0.0000 -0.0000 0.0000 -0.0015
0.0000 -0.0000 0.0000 -0.0000 9.2972
Thank you and best regards, Joo
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Dear Joo ...
Check your the step of discretization and linearisation of your simulation.
Regards
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Hello everyone, I hope you have a good day,
As we all know, the lateral dynamic system of vehicles has two output, lateral error and heading error, and we have one input, which is steering angle, I always have one big problem:
How to Design a Controller to have zero steady-state error, when I have XY reference path?
I designed a controller to track the heading, but when the vehicle gets departed from the path, as it does not have any sense of lateral error, it will not come back to the path, it will just follow the heading with some offset.
I read a lot of papers in this area, but none of them talked about XY reference paths.
I add a photo to clear up some points, please check the attached file.
Thanks in advanced,
Arash
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I'm writing my thesis and I am searching for good software to draw control block diagrams!
Any suggestion?
Thank you!
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Tableau Desktop is also good one for drawing the scientific illustrations.
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.
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Discrete-Time Systems:
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I want to find PID parameters to regulate my system.
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Manual PID tuning is done by setting the reset time to its maximum value and the rate to zero and increasing the gain until the loop oscillates at a constant amplitude. (When the response to an error correction occurs quickly a larger gain can be used.
The best method for tuning PID controller parameters is depend of your system
Regards
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I want to know all the things related and necessary which help me in control system field.
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You can use control methods in everywhere. Below, there are some areas:
  1. Power systems (smart grid , micro-grid , power generation , power devices (motors,...))
  2. Electrical drivers for electrical motors
  3. Biological systems
  4. Economic systems
  5. Social systems
  6. Robotics
  7. Aerospace and aeronautical systems
  8. Automobile industry
  9. Chemical Process
  10. Multi agent systems
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Hello everybody
I would like to link two topics, LCCA and BIM, each of which deals with "structural and earthquake engineering" and "construction management" in civil engineering, respectively.
I am trying to investigate on LCCA of a structure equipped with Tuned Mass Dampers (TMDs) based on principles of Performance Based Earthquake Engineering (PBDE) for different seismic hazard levels (this issue is related to structural engineering). So I intend to use BIM to create a more realistic cost model including other costs are related to this topic.
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I suggest that you use the 5D BIM technology, which is related to the cost of construction elements. You need to model your project using software as revit, and then link the model's elements to the cost and time schedule using software like Naviswork. This will give you visualization for the construction phases and the project life cycle.
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In order to get a better conditioned A matrix, the absolute mean of the eigenvalues of the A matrix should be one (all eigenvalues are between -1 and 1, so within the unit circle and the absolute mean is 0.4389). This could be done by scaling the time.
For the following continuous-time state-space model:
dx/dt = Ax(t) + Bu(t)
y = Cx(t)
the state-space model will look like:
dx/dtau = (1/lambda_avg)*Ax(tau/lambda_avg) + (1/lambda_avg)*Bu(tau/lambda_avg)
y = Cx(tau/lambda_avg)
with
lambda_avg, the absolute mean of the eigenvalues of the A matrix
tau, the new timescale
tau = lambda_avg*t
However, I want to scale the time of a discrete-time state-space model in order to get a better conditioned A matrix:
xi+1|k = Axi|k + Bui|k
yk = Cxk
How could I do that in the same way as for the continuous model?
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Hello everybody,
I have observed a bit confusing behavior of my system response (or may be I am missing something).
I have a transfer function in S domain converted to Z domain with a 1kHz sampling frequency at the time of conversion using matlab, When I embed this discrete version of the transfer function to my system which is also sampling on the same frequency of 1kHz. The system works the way as expected (i.e. the step response is the same as that of the s-domain analogue controller).
But if I increase the sampling frequency of my system while using the SAME discrete transfer function that i just converted from s to z domain with a SAME conversion sampling frequency of 1kHz , the step response gets further faster.
My question is that, why the discrete system gets faster response than the analogue one, despite the transfer functions of the analogue controller and the discrete controller are the same.
What I understand, the step response of any transfer function should remain the same in either case (i.e. either the function is in s-domain or in z-domain) the response should be the same ?
Does this mean the digital controllers have the ability to fast the response of the same transfer function by changing the sampling frequency of the system?
It is important, not to confuse the system sampling frequency of my u-controller at which the u-controller is collecting the samples from ADC, with the sampling frequency that I used as a parameter required to convert the s-domain transfer function to z-domain transfer function.
I thank you all for your time.
Regards,
Iftikhar Abid
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The conversion from the S-domain to the Z-domain can be accomplished by using the bilinear transformation.
- A transformation for S to Z
S= (Z-1) /(Z+1)
- And frequency prewarping
w analog = tan wd/2,
where wd= 2 pi f/fs
As one sees if one changes fs , one has to change w analog as a consequence of prewarping.
Best wishes
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Would anyone help me to understand the difference between energy signals and power signals (with examples to each of them), and what is the physical intuition behind the relation between the auto-correlation function of a signal and its power spectrum density?
Thank you in advance.
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When the energy of a signal is finite, but power is zero, such a signal is called energy signal. for example- a pulse has a finite energy, though power is zero.
On the other hand, if the energy of a signal is infinite, but it has a finite power, it is called as power signal., for ex- sinusoid is a power signal.
The auto-correlation function is simply the convolution of the signal with itself (not flipped), where delay/lag is the parameter. Here we try to find how much a signal overlaps with itself when lag parameter is varied over time. Its Fourier transform is power spectral density, which also does the same thing in frequency domain. So, at t=0, the auto-correlation function provides the energy or power of the signal x(t). (based on whether x(t) is a power or energy signal) which is same as the power in frequency domain obtained by integrating power spectral densities for all frequencies.
so, basically, both tell the same thing, one with respect to time, other with respect to frequency.
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I want to start to work on some stepper motors bipolar with arduino mega and ramps 1.4 but I don't know how to do it. Can anyone explain how to do this?
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I don't understand exactly what you mean? What is your goal? What do you want to do?
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The specifications are in term of R, L, B, J, kv, kt
The max output force of  electromechanical  braking system is 3500N
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Hi, I initially face a same problem in my research. It solved :)
Kindly refer my publication attached.
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I'd like to know about the best method to defined a fuzzy rule base for fuzzy logic controllers, most of references said experience knowledge is the best way, but what are the other parameters?
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Useful link from , thanks for sharing.
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What is the typical pitching speed of modern MW turbine blades and do this blades pitch fast enough compared to changing wind speeds?
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Significantly very fast. Standing at the control panel of a Vestas 850 kw , I saw the display was showing the instantaneous power production and pitch angle. The display was updating either every second or half second and each reading gave different readings. so a time constant for the pitch of under a second, for 40 m blades is astonishing!
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I have a brushless gimbal motor (with 12N14P windings) whose rotor shaft position is measured by means of a high-resolution absolute optical encoder. (The motor has no hall-sensors)
The amount of current fed through the three field windings are independently controlled by 16-bit DACs. (i.e. not just PWM)
What control algorithm should be used to implement precise position control of this closed-loop system, and what auto-tuning technique should be employed?
I "think" that the 12N14P winding scheme means that one full rotation of the field winding signal produces one 1/14 of a mechanical rotation. (but I could be mistaken).
It is not known what the physical angular offset relationship is between the field windings inside the motor and the zero-datum of the absolute optical encoder attached to the rotor shaft. I suspect that the auto-tuning technique will need to perform an experiment to determine this angular offset if the control algorithm is to be able to produce a field vector that leads the desired position by 90 degrees to achieve maximum torque.
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From the IMU we get position and velocity after sensor funsion. The input variable of the plant seems to be the speed of the gimbal motor (since its driven by 3 sine waves), not the voltage as usual in a brushed dc motor setup. So one can not just implement a torque control for holding the position. When I investigated the Storm32BGC, it looks like the PID does influence the position and the speed at the same time: Fast movements leads to fast speed corrections, but also the deviation from the stationary position leads to a given speed.
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On what parameters the selection of continuation method depends ?
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We have proposed a numerical method (denoted as MEM) for solving the
Nonlinear Dynamic problems. If you would like, you can view our published articles in this field entitled "dynamic analysis of SDOF systems using modified energy method". By the way, the presented idea is also generalized to MDOF systems in another study, which is available on my research-gate account.
if you need more information, please let me know.
Regards,
Jalili
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To design a controller for multi-degrees of freedom actuators which type of controller is better (Sliding Mode Controller or Backstepping Controller)?
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There are 4 issues I have seen in this discussion:
1. Backstepping can compensate theoretically exactly only uncertainties decreasing together with the state variables. No comparison between backstepping and SMC in this sense.
2. Matched and unmatched uncertainties
For perturbed chain of integrators there are no unmatched perturbations. If you will differentiate the output till the system order all the perturbations will be matched! That is why the only reasonable to control the systems with unmatched uncertainties is a combination between backstepping and SMC, where backstepping compensates state dependent part and SMC(see Estrada et al IJRNC,27(4),2017,DOI : 10.1002/rnc.3590,Automatica 2010(11), TAC 2010(11), J. Davila TAC 2013, Ferreira et al Journal of Franklin Institute, 2014, 351(4),doi:/10.1016/j.jfranklin.2013.12.011, Automatica, September 2015, Vol. 59, 10.1016/j.automatica.2015.06.020)
3. SMC can not be smooth. Sliding mode (for definition!) is a motion on the sliding surface!
4. Chattering
4.a. There is no way to keep the sliding mode and eliminate the chattering.
4.b. It is wrong opinion that it continuous HOSM controllers (like super-twisting, Kamal et al DOI:10.1016/j.automatica.2016.02.001, Torres et al doi :10.1016/j.automatica.2017.02.035, Laghrouche et al TAC,2017) everytime produce less chattering that discontinuous ones (see https://www.researchgate.net/publication/317229996_Is_It_Reasonable_to_Substitute_Discontinuous_SMC_by_Continuous_HOSMC).
It is true for the systems with fast actuators only.
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Where can one get measurement data for ieee 34 bus radial distribution system ?
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I am making a small prototype, that consist of small compact size aerostatic bearing with active compensation. I have to control eccentricity of shaft by using active compensation. For this purpose I need a laser sensor to measure shaft eccentricity that varies from 0 to 100um. one possible suggestion is to use laser sensor of omron company but problem is that my current location is china and omron company said it will take you 5 month to receive it. Please suggest me some other possible ways so that I can finish it before time
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If you want non-contact sensor, then proximity displacement sensor such as Bentley Nevada proximity sensors and Omega non-contact sensors can be used, they are cheaper than Laser sensors and have excellent accuracy:
If contact is permissible then you have wider options and LVDT sensors can be used, they have good accuracy and cheaper pices:
or search google or alibaba for LVDT sensor
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the coefficient of the plant should satisfy what kind of requirement ? and can you give some exampled?
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It is generally difficult to stabilize unstable high-order non-minimum phase plants with the 'ideal' PID controller. Take Lakshmanaprabu's model as an example, which has a real pole and a real zero in the right-half plane:
Gp = (5⋅s − 1)/(16000⋅s4 + 41200⋅s3 + 2940⋅s2 − 152⋅s − 5).
It is possible to stabilize the plant with a cascading compensator
Gc = k1 − (k4⋅s2 + k3⋅s + k2)/(s3 + N3⋅s2 + N2⋅s + N1)
where
k1 = −4.4690e+04
k2 = 4.9923e+04
k3 = −2.6980e+05
k4 = 1.1096e+05
N1 = −1.1172
N2 = 6.0334
N3 = −2.4079
The closed-loop transfer function (Gc*Gp)/(1 + Gc*Gp) is a 7th-order system:
Gcl = (−2.235e+05⋅s4 + 2.793e+04⋅s3 + 4190⋅s2 − 139.7⋅s − 5.586) / (1.6e+04⋅s7 + 2674⋅s6 + 270.4⋅s5 + 17.88⋅s4 + 0.8151⋅s3 + 0.02545⋅s2 + 0.0004759⋅s + 4.249e-06),
which has two real zeros in the left-half plane and another two real zeros in the right-half plane. Cancelling the two real zeros in the left-half plane with a pre-filter
Gf = 4.249e-06/(s2 + 0.125⋅s + 0.0025)
applied to the input command outside of the feedback loop yields Gclf = Gf*Gcl
Gclf = (−5.934e-05⋅s2 + 1.483e-05⋅s − 5.934e-07) / (s7 + 0.1671⋅s6 + 0.0169⋅s5 + 0.001118⋅s4 + 5.094e-05⋅s3 + 1.59e-06⋅s2 + 2.974e-08⋅s + 2.656e-10)
Computing the DC gain of Gclf (−2234.5) and placing a reference scaling factor "1/dcgain(Gclf)" ensures the unity gain when a unit step input is applied.
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Hi,
Does someone have any experience of using PSVM for fault detection?
Thank you for the information
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Dear Faeze Sdi,
Why proximal SVM are you using? You may try other algorithms for fault detection.
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Hello,
hoping that you will be in good health,
i have a 7-DOF independent wheel drive electric car model can be linear/nonlinear with longitudinal velocity, lateral velocity, yaw rate and angular rotation of the four wheels as the states of the system. the input to the system is the torque of each wheel .
i already designed a controller linear(LQR)/ nonlinear(SMC) which will turn the car with 90 degree yaw angle.
i want to find the trajectories/conditions that will achieve the control objective in minimum possible time/distance and minimum possible yaw rate, its kind of optimization "i think" can you please suggest any method or technique for doing this problem, or any starting point, i am using MATLAB/SIMULINK for my simulation ....
actually i am following the work done in this paper but they used some other tools for there work.
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You can find a fully developed 14-DOF vehicle model in MATLAB with a time efficient suspension model and a reprogrammed full set MF tire model in https://arxiv.org/abs/1803.09411, in addition, this work formulated and solved the complicated optimal design and control problems of a 4-IWD electric race car on a given track in curvilinear coordinate system.
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Dear all;
1: I used SVM to fault detection, now I want to figure out effect of fault in 10 seconds time slot of 60 seconds such that I have a window of data with 10 seconds length like 0-10 seconds,0.005s-10.005 s, 0.01s -10.01s ...60s. and I want to use SVM for each 10 s window of data.
I have some data in excel file which is divided to two parts; upper section is normal data and lower section is fault data and I have 6 features. Entirely I have 24002 data. I wrote a piece of code but I'm not sure if it is correct or not and I want to know how can I correct it? 2:I would like to know how can I divide my data to train and test in for loop for each window?
clc;clear;close all;
T=2001; %length of data in 10s (Window Size)
X=xlsread('Book4');
K=(0.5*length(X))-T+1 % Number of repetitions
window=zeros(2*T,6);
for i=1:K
window=[X(i:i+T-1);X(i+12001:i+12001+T-1,:)];
%% Data Normalaization
m=length(window);
Mean_data=repmat(mean(window),m,1);
Std_data=repmat(std(window),m,1);
data_norm=(window-Mean_data)./(Std_data);
end
I'll appreciate your help.
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Dear Jiri Kovar,
I don't know exactly about GETFRAME. Would you please explain more?
I want to create motional time window in order to fault detection in each window.
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Sir,
I am unable to solve second ramp response. I need the derivation with partial fraction.
Thank you
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For step response, input R(s) = 1/s; where as R(s) = 1/s2 for ramp response. Using this input you may derive those responses by standard methods (using Laplace transforms). Also you may refer to Control Systems Principles and Design by M. Gopal, 4e, pages 92-93. Further if your system is LTI, you integrate the standard step response then you get the ramp response.
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OpenDSS is a wonderful package, but it is not suitable for simulating some special features of railway traction network, it would be fantastic to have something similar related to Railway power systems. What do you think?
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I totally agree with you in that
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I have designed a controller using Integrator backstepping method and that controller is based on Lyapunov Theory. I have a question How I can check stability of resulting controller?
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Hi Waheed,
Thanks for your reply.
Since you have designed a Lyapunov-based integral backstepping controller for the 4th-order MISO system, what exactly is your difficulty in checking the stability of the control system?
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