Questions related to Control System Design
I'm looking for a exhaustive paper (or book) regardind a four (or two) wheeled robot trajectory control system in order to reproduce and fully understand the kinematics and control system equations.
My rover has four motor, one for wheel, and turns through a wheel speed control.
Would be amazing find the PID control design on the angle and speed control as well as the trigonometric equations of the robot trajectory.
Thank you very much
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)
Hello, Can we find Kp, Ki, and Kd values of PID, Lead-lag, or Type2/Type3 compensator? I have designed a type2 compensator for my system but now I need a PID controller for the same system can I access Kp and Ki values from the Type2 compensator? Please guide me
Dear Esteemed Researchers,
I have a mathematical model of a Plant. I want to implement two different controllers and see the response of system in tracking a specific reference. I would like to analyze the transient time response of the system for both the controllers. I don't mean to just check the response in simulation I want technical analysis using tools such as eigenvalue analysis. What tool can help me build up the evidence for best transient time response.
I am trying to discretize a continuous time state space model using the following code
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?
I am working on a project in which I need to control the duty cycle of the pulse given to mosfet in an AC to DC converter.The mosfets are connected to LCL filter to give a regualted 5V.The output voltage and a reference of 5V error is taken and a compensator is connected.The output is compared using PWM and then sent to mosfet.Do we need mosfet driver in between?What kind of mosfet driver should I use in multisim?Can I get any reference?Should we solve this using bode plot?Should I use PID controller to decrease the error and should I simulate in MATLAB using PID controller ?As I find it easy
Hey! I'm in the work of designing a controller for a zeta converter, it is a fourth-order system.
I tried ways like the Ziegler-Nicols method, Root locus method using Control System Designer in Matlab. But couldn't get any satisfactory outcome. My bad.
I have two PI controller running in parallel both controls the same output variable, based predefined input conditions I would like to transfer control from Control A to Control B without any variation in the output response. would be great to get any suggestion on efficient way of doing it.
Using Matlab Simulink as implementation plattform
I am working on a project where we are going to develop controller for batch fed biomass boiler.We have done some experiments in our lab setup and those experiments are time consuming.I want to know whether
there are software packages which we can model and simulate the biomass combustion and as well as the control system modelling.
I want know about both commercial and opensource software packages
I am interested to simulate distribution networks with distributed generation utilizing custom controls. Simulink is quite versatile in control system design and is friendly for people preferring visual approach to programming. But I am not always satisfied with how it solves power flow for detailed network models.
Lets say that I am looking for more reliable power flow solvers, but with control system design versatility of Simulink (preferably with visual programming). Any suggestions?
Given a system with redundant actuators, what would be the names of techniques that I could research to use each actuator for different frequency bands?
To illustrate the problem with a simple 1-dimensional problem, consider the attached picture. We have a mass m moving in 1-dimension connected to two redundant actuators. We want to regulate the position x while rejecting a disturbance Wd. In addition, we want to use the first actuator U1 to reject low frequency disturbances and the second actuator U2 for high frequency disturbances only. In other words, we do not want to use the second actuator U2 at steady state.
So far, I have come across Härkegård's work, such as , that explores dynamic control allocation. This discrete-time technique provides a way to penalise both high and low frequency usage of an actuator by adjusting the weighting matrices in its quadratic-programming cost function. They illustrate this technique by designing an aircraft control system for a fighter aircraft with a delta-canard configuration. The controller is designed to result in no canard deflection at trimmed flight to achieve low drag.
I am currently looking for other techniques that could be used to 'partition' the frequency usage of redundant actuators in order to get a more holistic view of the topic before committing to a single technique. I am looking at both techniques that separate the controller design and control allocation problems and ones that combine both.
Any suggestions of technique names or terms I could research would be much appreciated.
Thanks in advance for any suggestions.
 Härkegård, Ola. (2004). Dynamic Control Allocation Using Constrained Quadratic Programming. Journal of Guidance Control and Dynamics. 27. 10.2514/1.11607.
I some papers, the mean square error is considered. In some other, the mse is normalized by dividing the error by the (total sampling instants x the total length of the reference trajectory).
Which solution does represent the factual error?
It is seen from that most of the control system design has to be done in time domain and frequency domain design is less preferred. Could you please put light on the reason behind it??
Thank you in advance..
I am working in the field of control system design. So, I need human immunity dynamic model for further research in my domain. Please share the above one and also, collaborate in this work.
Thanking you in advance.
What analysis tool is most suitable for transient-state analysis and designing control to mitigate those transients in power distribution system? I am planning to carry out transient analysis caused by sudden increase in load on distribution feeder and want to control those transient by charging/discharging the battery storage system. Our load has a high ramp rate and high magnitude which could cause these transients in the distribution grid voltage profile.
Your project sounds very interesting - maybe a weight change system like this can be modified to serve pigs? https://youtu.be/MniFOpO3jws
This very durable and autonomous device can support fluid flow/percolation while measuring mass, and I propose that this could be beneficial to your PigSys. regards Stephen
Should they be designed for predefined socio-technical functionality or for context-dependent utilization of stimulated/acquired social, cognitive technical affordances?
As I have implemented in the attached picture, I'm making a simulink model and it keeps on giving an error:
Error in default port dimensions function of S-function 'FeedbackLinearization/Controller'. This function does not fully set the dimensions of output port 2
I toggled the signal dimensions display on and then I noticed that for my "error" signal, the output is of dimension 3 but it somehow transforms in dimension 1. (See the picture)
Can anybody please help me? I'm very confused
In your opinion, what are the main challenges currently for the design of autonomous vehicle systems? Answers can be related to hardware, software, controls, societal impact, etc.
Secondarily, what are the main considerations that can be relaxed or approximated (to save design time and cost) for systems that will not directly interface with humans?
I have a question about the circle of friction or Kamm circle. This circle is used in vehicle modelling, but I did not understand this well. I say my own opinion, please let me know if I am mistaken.
vehicle friction force at tire contact patch divided into two forces, lateral and longitudinal forces. As the coefficient of friction is u and the normal force is N, then the maximum of friction force is F_tot = uN. Now F_tot is the radius of the Kamm circle (?), then F_x and F_y are longitudinal and lateral forces, so ( F_x^2 + F_y^2 )^0.5 is lower or equal to F_tot.
If I was right, please tell me what is the use of Kamm circle?
Thanks in advance.
Kindly help me with the parameter selection of the value of gains of the PR controller.
Can there be a system which has unstable closed loop behaviour and a stable open loop behaviour ? Do they form a separate class of system?
I am unable to solve second ramp response. I need the derivation with partial fraction.
I work now about the integration of PVs panels in a distribution system, but to do that i need to calculate the PI parameter controller for voltage outer loop and current inner loop in the Vsc Control. but I don't know how calculate the value of this parameters. I am looking forward to your help! Thank you very much!
The voltage outer loop and current inner loop are attached to this mail.
Is it possible to drive a piezoelectric stack with just DC.. ie. if you want to use a piezo to move something a set distance can you just apply a constant voltage to keep the piezo "activated" at the desired length, or do you always have to drive them sinusoidally. For example with the piezo microscope stages are they AC driven with some complicated synchronising stuff to only take images when they are at the right place, or fixed in a position with a DC voltage?
I'm trying to design a controller for a flexible arm. The dynamic equation which describes the system is
T (t) = (I + 1/3 ρ*L^3) θ¨(t)+ρ Integration from (0 to L) x ¨ y(x, t) dx
+ m*L*(L ¨ θ(t)+ ¨y(L, t )).
I, ρ, L, m are constants
The variable y(x, t) is the deflection of the arm at a point located a distance x from the beginning of the arm
θ: the rotary angle of the arm from its reference position.
My question now is how to transform this equation in frequency domain using Fourier transform
Detailed Description :
I am working on steering wheel angle sensor that measures absolute angle of steering wheel. As steering angle sensors uses gears and several joints which is totally hardware related so in spite of calibration in start with the passage of time due to usage of mechanical parts and also due to some environmental and road conditions some errors occurs in the values of sensors (e.g. offset, phase change, flattening of signal, delay).
In short due to these errors in the measurements our aim gets distracted means If I am viewing velocity vs time curve so if in the original or calibrated sensor in short close to ideal condition sensor my velocity shows a peak in amplitude but due to error (hysteresis) in measured signal I am not getting peak in velocity curve or I am getting flattening of curve so it will affect my final task.
I have a tolerance let say 1.20 degree for hysteresis so that’s why I am having detailed idea about my signal and want to observe my signal if some changes means offset, delay, lowering has occurred in my signal or not. This will not only provide me an idea that whether to lessen the amount of sensors used for my task or made some changes in hardware of sensor to lessen the amount of hysteresis or do some other actions to reduce it.
What I have done uptill now in which uptill now I am not sure that whether I am right or wrong. I am getting some values for hysteresis but I have few questions regarding those techniques. If someone provides me an idea about it how to improve these techniques or provide me a better approach then it will be nice and great guidance.
I have an ideal sensor signal (under ideal conditions which we want) and values from 1 sensor I have data of 6 different drives from car. I am explaining just 1 example of my first drive and its relation with my reference sensor data.
Given the data reference signal and sensor signal data of size 1x1626100 and 1 x 1626100 double for one reading from sensor but in all readings values from Ideal and measured signal w.r.t to time are same.
In short I want to find out the Hysteresis difference of sensor signal from measured signal.
I have applied few data estimation techniques to accomplish my goals.
1- I have applied Gaussian Technique to estimate error in my data but I am not satisfied with it as I am not getting some good values or expected values with it may be due to outliers or some other errors.
I have subtracted (Ref – measured value of signal). Calculated mean of difference signal after applying my limitations, Standard Deviation of difference signal after applying my limitations, then make a Gaussian Curve along with mean and standard deviation. Made 2 lines one for mean+ standard deviation and 2nd one is with Mean – Standard Deviation and distance between +ve Mean_std and –ve Mead_std is called Hysteresis (Loss).
Please have a look at the attached figure. I have attached figure for 3 modal Gaussian curve but in some diagrams just like picture 3 my data is shifted. Can anyone tell me the reason why it is so and how to erase it because it is occurring in all diagrams but in this figure 3 it was clear.
2- In this method I have applied Regression lines Technique (On upper and lower values of difference signal).
I took difference of my signals (Ref – measured value of signal after applying my limitation on signal).
Applied regression technique above and below the difference signal means on upper values and on lower values separately and difference between upper and lower values regression lines is called as Hysteresis (Loss). Please have a look at figure 3 and 4 for clear view.
The Problem here with this technique is that I define the values for upper and lower regression line by myself after looking into data like up= 0.08 , low= -0.08.
3- I have also applied RMSE technique but have few questions that are confusing me.
As I am dealing with static data so I considered my Reference signal as actual valued signal and my measured valued signal from sensor as measured values and apply RMSE formula on that.
RMSE= square_error = (sig_diff_lim).^2;
mse = mean(square_error)
msedivided = mse/numel(drv(2))
rmse = sqrt(mse)
4- I have also applied correlation function but I think it is not working well with my data.
But it gave me some good insight about data.
Some Questions that also need clarification if possible:
1- What is difference between RMSE and MSE means I know basic stuffs but I want to know that what are the applications where we use RMSE or MSE and which will work in my case for my data.
2- I have now explained Gaussian, Regression technique, RMSE. Just one Request .Can someone explain me which Technique is the best to use because I have mentioned my issues in Gaussian and Regression Technique above. Just some explanation will work for me .Means Pros and cons of above mentioned technique.
I hope that I remained able to provide you the clear idea and detailed review what I want to do and what I am expecting and I hope to get some positive and valuable response from people.
Sorry for providing a long story but As I am not too expert in these as I am still learning so if I will get some useful responses it will improve my knowledge and also help me to accomplish my task/Goal.
Thanks for cooperation in advance.
I am working on high bandwidth controller design for high speed scan mirror mechanism for satellite. The structural frequency (or vibrational frequency) for this system is coming within the desired bandwidth for attaining the high speed motion.
I would like to analyse the stability of a closed-loop system in which the controller is built around a Smith predictor. I am interested in particular with the stability analysis with respect to uncertain time-delay in the plant. Thank you.
I have a question on observer design . I am working on a state space controller that involves an observer . I started with designing a state feedback controller without and observer . It works and meet my design requirements. But some of the states are not measured, I need to include an observer to estimate the states . But the problem I am having is my observer is able to estimate states without L matrix , meaning open loop observer working excellent , which seems too good to be true. My understanding is Luenberger observer uses system output which includes extensive infor abou the states and involves calculating gain L. I have not solve for L I think my gain will come out to be zero , as my states match exactly with open loop observer . Is that possible ?
I acquired some input and output data sets from a PID closed loop control biological system which the input is brain stimulation and output is the measured blood flow. I tried to use system identification toolbox of matlab. The results turned out that a second order process model can model it pretty well.
I have heard Model Predictive Control can provided better control outcome under two condition the model should be accurate enough and the plant needs to have delay.
First question I have is how to define the accuracy of modeling/system identification and how accurate it needs to be for MPC to have better control outcome?
Second question I have is how can I measure the delay of a system by using input output data sets?
Bode plot, plots the magnitude and phase of the open loop transfer function. Nyquist plot, plots the Real and imaginary parts of open loop transfer function. In principal, both have the same information. But for stability analysis, mainly for systems with zeros and non-minimum phase systems, Nyquist plot is preferred.
Using Nyquist plot, one can tell the number of right half plane poles. But is there a similar method available while using Bode plots?
In designing an unknown input observer for the system, first, we need to show that the invariant zeros of the system must lie in the open left half complex plane and the observer matching condition is satisfied.
How can I check the first condition about the invariant zeros of the system?
Thanks in advance for any help.
In relay auto tuning of PID controllers, controllers are replaced by a relay in closed loop. For step change in setpoint, process variable oscillates and their period turns out to be a close approximation of the ultimate period -Pu, that Ziegler and Nichols (ZN) used for their tuning rules. And the amplitude of the process variable's oscillations relative to the amplitude of the control effort's oscillations approximates the process's ultimate gain - Ku, when multiplied by 4/π. Then ZN tuning rule is applied.
But theoretically, how a pure first order system (linear, no time delay - maximum phase lag will be only 90) oscillates at ultimate period (resulting from a phase lag of 180)? It oscillates in relay auto tuning method, but how it will be Pu?
Note: Also ZN ultimate gain method is not valid for pure first order systems - no ultimate gain possible here?
Thanks in Advance.
Could some explain the difference between the controller and compensator in control system design?
Since similar behavior is there for the Proportional Integrator and Lag compensator?
Question 1:What is the reason for a BIBO stable LTI system that all the roots of the characteristic equation have negative real parts?
Y(s)=T(s)*R(s)= N(s)/D(s), where T(s) is closed loop transfer function and R(s) is input to the system. For y(t) to be bounded, all the roots of D(s) should lie in left half of the s plane. It can have roots on imaginary axis (but not multiple root on same point). According to BIBO output it should be bounded for every bounded input. So poles of system transfer function should lie in the left half of the s plane(excluding imaginary axis as bounded input can have poles on imaginary axis). Is the laplace transform table only proof for this?
It is the same thing extended for Polar and Bode also.They both are not complete plots. For an unstable open loop system, they cannot predict the stability of a closed loop system. In books they mention polar and bode can be applied to minimum phase systems, but stable open loop systems may have zeros in the right half of the plane. So in polar and bode open loop transfer function restricted to minimum phase systems or systems only with poles only in the left half of the plane?
In Nyquist it is clear that it is an extension as it comes from Cauchy's argument principle.
For closed loop systems having repeated roots on the imaginary axis is the Nyquist theorem valid?
Please elaborate and correct me if I'm wrong somewhere.
The seventh order transfer function is [-1496.8 (s^2 + 7.942s + 21.66) (s^2 + 0.6747s + 142.9) (s^2 + 119s + 4991) ] / [(s+2.681) (s^2 + 21.06s + 192.9) (s^2 + 1.836s + 147.7) (s^2 + 47.69s + 9205)].
As I understand, stability of such a closed-loop system is discussed in two steps.
1- observer error dynamics must go to zero exponentially fast.
2- state variables must always remain in the attraction region of the controller.
Khalil ("Nonlinear Systems" 3rd edition, page 617) has explained this in a very complicated way.
Can anyone give a better and formal explanation?
so can we say that from above statement that a large resonance peak in frequency response corresponds to a large overshoot in transient response?
is there any book available regarding close loop control of electical machine(dc m/c, PMSM, BLDC, IM, SM etc) which includes machine modelling along with control system design like we have erickson maksimovic'in Converter control area???
For example when you want to design a high speed response controller with minimum steady state error ( in network modem) the choose of a high-gain is a good thing, but what are the caveats from the viewpoint in control theory?
sensorless vector control drive How can I calculate speed of an induction motor from current and voltage vectors? please provide the equations if possible,how to impliment in matlab?
As i want to add the simulink model of PMU to my simulation but From where I can get the PMU simulink model?or from and how I construct the simulink model of PMU in MATLAB?
I have a Reaction Wheel hardware unit. I have been working on the estimation of internal parameters using RW outputs using Matlab and Simulink. Now I would like to be able to test it with hardware. The model I have from the RW is by Bialke. The hardware model is a little bit different but should be bale to manage the estimation process regardless. My challenge is how I can change/manipulate internal parameters change in the system so that I can test estimation algorithm with real hardware-in-the-loop.
If anyone has experience in this area please let me know. Also if you need more information please let me know.
I have a previous knowledge of the system, so I've the lower and upper bound of the frequency response test.
I'm performing the response frequency test, as follow:
The input to the system is given one frequency per time, and after X cycles at the same frequency,the frequency is increased by a factor, F.
The X cycles are chosen appropriately to let the transient of the system vanish, and the increment F is chosen to have enough frequency to recreate the bode diagram.
To get the gain and the phase of the system for a given frequency, I've chosen only the portion that the system is in the steady state, and after I applied the least square method to the input and measurement (output of the system).
My doubts regarding about the implementation in the real world, because I cannot sampled the output and write in the input at the same time. Then, the input u(k) and output(k) are not synchronize.
I suppose the phase of the system in high frequency may be unreliable due to this problem. But, what is the correct sequence to minimize the undesirable effect on the test, without increasing the sampling frequency?
Do the calculation of the sine - Write at the Input of the system - Read the output
Read the output - do the calculation of the sine - Write at the Input
I should compensate the zero-order-hold, during the phase estimation? I mean I should increase the phase by a factor ws*T/2, where ws is the sampling frequency?
Thank you in advanced.
(like stationary signal, time correlation...)
Control system model identification using input and output signal.
Thanks a lot
How can I minimize J for finding K1 , K2 , K3 with de algorithm.according to photo
Guidance: Due to the variable j in terms of k1, k2, k3 is optional comment plant should face denominators grade 3 or less than 3. Ss command values of A, B, C, D obtained initial values of X1, X2 .X3 is also optional.
A, B, C, D is selected optionally.
I am implementing Kalman Filter on an Android device to get rid of noise generated due to double integration of accelerations from accelerometer. The aim of my project is to control the position of a model car so that it follows a specific trajectory. Kalman Filter predicts the position from some reference model to estimate the position in a recursive way. I can also take measuremets e.g from another sensor lets say, gyroscope, instead of car position from the physical model which could also be regarded as sensor fusion. The scenerio for first case could be as follows.
First step is to create the phycial model of the car. well as I am using an RC car. The input is the speed command to the wheels and output is the acceleration from the sensors. Which are the same as meaurements in the Kalman filter. I am not sure if this modelling approach is right? Does any one have experience in this area? The equations which I have created so far are as follows:
x(k) = x(k-1) + dt* derivative_of(x(k-1)) + velocity_of_car@(k)
derivative_of(x(k)) = derivative_of(x(k-1)) + dt/2* velocity_of_car@(k)
Where derivative_of(xt(k)) and xt(k) are the only two states of the car under considerations. Please first tell me if these equations are correct. and then if my approach towards Kalman Filter implementation is correct.
Given a non-linear system, where outputs of the system are 4 of its state variables. We need to design a state (output) feedback control with its linearized model. Is it possible to design such feedback control ? if yes, How ?
Hi, would some one help me classify the different methods employed to determine the 3D pose of camera setup from images of captured object of interest?
Suppose that you have a sensor, that you can't change the sample rate or any other feature including the anti-aliasing before the signal be sampled.
Beside this, suppose that, the control loop of the system runs with a slower rate than the sensor, and you cannot change the control loop rate, as well.
Now, assume that the sensor rate is multiple of the control loop rate.
Then, suppose that, after 5 samples of the sensor, the control loop runs once using the latest sample from the sensor (observation: the 5 five samples are stored).
As far I understand this characterized the down-sampling of the signal, and it produces the aliasing effects over the signal.
Then, how this effect can be minimized? Should I have to put a digital filter before the control loop?
firstly extracting the model uncertainties out of the nominal plant and use a weighting function to regulate the norm of the uncertainty block Delta within 1.Let's say z_inf to w_inf is Delta, and w_inf to z_inf is Tw_inf,z_inf(transfer function). According to small gain theory, the norm of Tw_inf,z_inf should be less than 1. Then the control goal is to design a controller(either output or state feedback) and make Tw_inf,z_inf less than 1. I'm wondering whether this controller always exist, or what are the requirements for its existence, Sorry if I made any conceptual misunderstanding.
In Ruth-Hurwitz algorithm one can determine how many unstable poles are in the system, due to the sign of the first column coefficients . I was wondering if there are any similar idea in Jouri algorithm.
thanks in advance,
I need an advice. What is the most efficient way to implement real-time control algorithm which needs to perform the following three steps every 5 minutes:
1. Read measurements from data base,
2. Based on measurements calculate control variables,
3. Write calculated control variables to database.
Thank you in advance.
we designed a controller for each loop individually for controlling the multivariable control system by allowing the interaction amid the variables. Now the question is how to measure the degree of robust stability of multivariable system. Is it measured individually to each loop or over all system. provide any supplementary document.
I want to design a controller for a model that has an integrator.For this reason, i would to design a PD controller instead of PID and so on. almost of books and refs discuss about tuning rules of PI and PID controllers. Is there any rules about tuning of PD Controller?