Publications (16)6.22 Total impact
- [Show abstract] [Hide abstract] ABSTRACT: The goal of this project is to design and build a dual-axis drive system for an electric bicycle. The computerized control for the electric bicycle utilizes a firmware-based system, with the vehicle's electronic control unit (ECU)and most of the signal processing circuits implemented using a Programmable SoC (PSoC). This special dual-axis driven electric bicycle has many advantages over electric bicycles currently available on the market. To be able to have both wheels drive the vehicle simultaneously, the speed controller must be designed with a very high degree of accuracy so that it has the ability to compensate for speed difference that might exist between the front and rear wheels. In addition, both wheels have breaks and kinetic energy recovery for decelerating or downhill riding. The vehicle has automatic cruse capabilities and can automatically switch to single front or rear wheel drive at medium or high speeds. This saves power and avoids any single motor driver overheating because of long term driving.
- [Show abstract] [Hide abstract] ABSTRACT: The firmware design is a tough task for university students because firmware combines hardware design and software programming. In this paper, a mixed-signal array IC chip called Programmable System-on-Chip (PSoC ® ) from Cypress Semiconductor is employed as a firmware platform for signal processing as well as digital signal processing practice. PSoC is a single chip with mixed-signal array as well as on-chip MCU. It provides a solution for integration of analogue and digital hardware as well as software programming. In this paper, practices of analogue filter design and digital signal processing by PSoC filter design for university senior students and graduate school students are introduced. This signal processing course modules can be divided in two parts: (A) Designing analogue filter with configurable analogue blocks in PSoC as the design practice for signal processing. (B) Implementing digital filter in PSoC with MATLAB FDATool toolbox as the firmware design practice for digital signal processing. Through the designed sections, students can study the process of designing analogue and digital filter in PSoC chip with the help of MATLAB toolbox. Students can actually experience the power of firmware and understand how to accomplish filter design projects.
- [Show abstract] [Hide abstract] ABSTRACT: An adaptive perturbation and observation (P&O) method for the maximum power point tracking of photovoltaic system is proposed with programmable system-on-chip firmware implementation in this paper. This proposed method holds the following merits: the control algorithm is simple and easy to implement, the power oscillation at the maximum power point and the tracking speed are improved, moreover the adaptive perturbation and observation method can track the new maximum power point rapidly when the ed to complete the boost converter circuit. Therefore, this proposed hardware structure might be the most concise circuit ever. The proposed circuit is tested and compared with the conventional P&O method. The performance of propose adaptive perturbation and observation method is 0.4 second faster and 4.9% output power higher than that of traditional P&O method.
- [Show abstract] [Hide abstract] ABSTRACT: A compact, reliable, and robust auxiliary vacuum brake system has been implemented by utilizing a programmable system-on-chip (PSoC). All the circuit elements in this control system are integrated into one chip without any external electronic components. Circuit as well as system is compact in size and concise in design. Also, Kalman filter algorithm is employed and implemented within PSoC chip by software to surpass the noises and disturbances from hostile surrounding in the vehicle. A prototype has been built and tested. Test results have confirmed that the performance of Kalman filter is better than that of low-pass filter. Furthermore, Kalman filter is capable of dealing with noises and disturbances from vacuum pump and other sources while low-pass filter is not.
- [Show abstract] [Hide abstract] ABSTRACT: In this paper, Kalman filter is designed and implemented on a heat deformation tester (HDT) to estimate the LVDT sensor information from a noisy measured data sequence. In simulation and test, the output response of Kalman filter can separate noise from reference signal and the outcome is closely matched with reference signal. The response of low-pass IIR filter is smooth and can also separate noise but some time delay is presented. The mean squared error (MSE) of low-pass IIR filter is 0.6354 while the MSE of Kalman filter reduces to 0.1467, a significant improvement by 4 times. Also, the computational efficiency of Kalman filter is better than that of low-pass IIR filter in this application. Both filtering algorithms are implemented and programmed into a heat deformation tester (HDT). The performance is impressive.
Conference Paper: An auto-tuning Grey-Neuro-PID controller[Show abstract] [Hide abstract] ABSTRACT: In this paper, we propose to add Grey prediction model GM(1,2) into the self-tuning Neuro-PID controller based on radial basis function (RBF) algorithm to improve the performance of the controller. Initially, the prediction of system output by the simple GM(1,2) model is added to the RBF algorithm as one of the inputs to enhance the performance of RBF neural network system identifier. The output of this GM(1,2)-RBF on-line learning system model is subsequently used to establish a set of updating algorithms for the gains of self-tuning PID controller. The detailed description of the proposed system structure and the design algorithm is given in this paper. The proposed auto-tuning PID controller via GM(1,2)-RBF algorithm is put into tests by Matlab simulations and motor speed control experiments by using Lab VIEW. The system responses of self-tuning PID controller based on GM(1,2)-RBF and RBF are compared. Both simulations and motor test results confirm that the proposed self-tuning PID controller based on GM(1,2)-RBF performs better than the one based on RBF.
- [Show abstract] [Hide abstract] ABSTRACT: "Carbon black" is the major influential factor in categorizing the quality rank of rubber. This paper presents a new approach to simplify the ranking procedure with limited samples by using Grey relational grading method while the ranking accuracy is ensured. The proposed approach is described as follows: First, rubber samples are sliced and snapshot into black & white images. These images are further enhanced by digital image processing methods before applying this new clustering approach. Then, the "carbon black" of a sampled rubber image is classified into ten ranks according to the method B of ISOH345 document. The measured data are processed by using the algorithm of partial Grey relational grading methods. The "carbon black" ranking of rubber is obtained by sorting and determining the maximum value of Grey relational algorithm. In order to verify this new approach, test results are compared to the results taken by standard statistical method as reference. The results confirm that this new approach can use fewer samples and preserve the ranking accuracy.
- [Show abstract] [Hide abstract] ABSTRACT: This paper proposes a design and implementation of an assist-mode, hybrid electric motorcycle (H.E.M.). The proposed hybrid electric motorcycle is a revised vehicle from a 50 cc motorcycle and designed to match up with a 100 cc motorcycle. In order to expedite the developing phase and lower down the cost, a master–slave tracking control method is utilized. A dc servo-motor is deployed to track the speed of the rear wheel of the motorcycle and to provide more torque through power composite into the rear wheel so that the performance of hybrid electric motorcycle can be promoted. The advance of performance as well as the energy saving can both be expected. In road trip experiment, the H.E.M. prototype achieves an average gasoline mileage of 46 km l−1 compared to the original 34 km l−1. The overall efficiency is about 35% lift. Experimental results confirm the feasibility and prosperities of the proposed hybrid electric motorcycle.
Conference Paper: Design an Intelligent Neural-Fuzzy Controller for Hybrid Motorcycle[Show abstract] [Hide abstract] ABSTRACT: The main propose of this article is to design an intelligent neural-fuzzy controller for hybrid motorcycle. A self-tuning PID tracking controller based on RBF neural network with Fuzzy current limiter is proposed to maneuver the motor and save some energy in hybrid mode. The outer motor control loop is designed to track down the speed fluctuations by Neural-PID controller. Besides, one inner loop is designed to limit the armature current whenever the power demand is diminished according to a set of Fuzzy rules. The proposed structure is put into tests by Matlab programming. Simulations confirm this RBF-PID controller with Fuzzy current limiter can save 23.5% energy for a tracking task.
Conference Paper: Design of Refined Grey Prediction Controller[Show abstract] [Hide abstract] ABSTRACT: The goal of this article is to offer an automatic PID parameter adjustment strategy by using a grey predictor model. The grey predictor model together with a first-order low-pass alpha filter generates effective estimated values of the plant output. The output error is then embedded in a control algorithm that automatically tunes the PID parameters. The resulting PID/Grey controller is shown to outperform the PID controller that is tuned via the standard quarter-decay ratio method. The paper gives a detailed description of the system structure, the design algorithm, and its implementation. Regulation and tracking performance of the proposed PID/grey predictor controller are illustrated by means of computer simulation tests in the Matlab environment. Finally, a temperature regulation example is built by using LabVIEW programming and tested to validate the performance of the proposed controller scheme.
- [Show abstract] [Hide abstract] ABSTRACT: The purpose of this paper is to design and implement a grey prediction controller (GPC) via LabVIEW as a test platform. Grey prediction model GM(1,1) is used with the aid of first-order, digital low-pass alpha filter to refine the estimation of the system response in advance. The prediction is then utilized to modify the parameters of PID controller. Hence, an auto-tuning PID controller according to the forecasting of system response is achieved. LabVIEW software programming with a data acquisition card (model DAQPad-6015) from National Instruments Co. is chosen to provide a high-resolution, however, time-saving solution for developing this auto-tuning control system. One temperature regulation example is arranged and tested to confirm this auto-tuning controller scheme. Test results of this novel grey prediction controller are derived and compared with traditional PID controller. The Grey prediction controller is far better than PID controller in the prospect of both the transient response and steady state response. Best of all, this auto-tuning regulator eliminates the hassle of human interference
Conference Paper: An Auto-tuning PID Regulator Using Grey Predictor[Show abstract] [Hide abstract] ABSTRACT: It is the purpose of this paper to introduce the advantages of grey predictor controllers. We adopt grey prediction to obtain simple and effective estimated values, and, with the aid of first-order low-pass alpha filter, greatly improve the accuracy subsequently used in the prediction for system response. The result will be in turn used to predict error and furthermore automatically adjust the parametrical values of PID controller, and accordingly will be able to deal with the possible variation of system responses at the very first stage. It can not only actively promote the responses efficiency of transient response, but also passively prevent disturbance. As a matter of fact, the highest demand of "plug in and play" can be met without any need to adjust the parameter. This paper will give a detailed specification of the system structure, the design, and the concept, as well as prove the modulation function of grey predictor controllers in unit step response by means of Matlab program simulation and mathematical argumentation. In transient response, it will effectively fasten rising time, shorten settling time, and oppress overshoot; meanwhile, in steady state response, it is able to reduce steady state error to zero and achieve what traditional PID cannot perform
- [Show abstract] [Hide abstract] ABSTRACT: The theme of this paper is to design a 'grey statistic model toolbox' via C<sup>++</sup> in the GM model, for easy studying and learning in the grey system theory. In the past research about the grey model toolbox, focused on case-by-case needs. Although all studies have shown good results, only the individual case results can be presented. The full details are still lacking. Therefore, in this study, firstly, the C<sup>++</sup> is used to develop a toolbox for a grey statistic model. Secondly the clustering of student's test score is presented as the sample, and the feasibility of the toolbox is implemented, creating this study. Through the results, the grey statistic toolbox in the GM field not only presents a lot of figures to make the results more clear, but also upgrades the analytical level in the grey system theory during the whole implementation of this approach.
Conference Paper: Hybrid electric motorcycle: A master-slave mode design[Show abstract] [Hide abstract] ABSTRACT: This paper proposes a design and implementation of a master-slave mode, hybrid electric motorcycle (H.E.M.). The proposed hybrid electric motorcycle is a revised vehicle from a 50 C.C. motorcycle and designed to match up with a 100 C.C. motorcycle. In order to expedite the developing phase and lower down the cost, a master-slave tracking control method is utilized. A DC servo-motor is deployed to track the speed of the rear-wheel of the motorcycle and to provide more torque through power composite into the rear wheel so that the performance of hybrid electric motorcycle can be promoted. The advance of performance as well as the energy saving can both be expected. In road trip experiment, the H.E.M. prototype achieves an average gasoline mileage of 46 km/liter compared to the original 34 km/liter. The overall efficiency is about 35% lift. Experimental results confirm the feasibility and prosperities of the proposed hybrid electric motorcycle (H.E.M.).
Conference Paper: The development of portable infrared color sensor[Show abstract] [Hide abstract] ABSTRACT: The purpose of this project is to design and implement a portable yet high resolution color sensor which can identify the color, and can discern the color difference between a new paint and the old one. The resolution is 1/256 in digit. This device can give the provider a handful tool to get the right color of paint when body job is needed. Also, this device can ensure customers their paint jobs are well carried out with the objective digital readout from the device. This device uses the infrared photodiode pair as the color sensor. One constant current source with feedback loop from one photodiode receiver to ensure a pre-fixed brightness of infrared light is emitted from the transmitter. Another photodiode picks up the reflected signal from surface in a pre-determined distance. The color difference can be seen as the amplitude variation of the reflected signal. This amplitude variation then feeds into A/D converter to quantifilize the color into digits, i.e. 0 to 255 in the resolution of 1/256. A single chip microprocessor takes in the information via its I/O port and compares the data with a built-in color look-up table. Finally, the identified color along with its digitalized brightness readout is shown on a LCD display controlled by the micro-processor to carry out the color scrutiny scheme
- [Show abstract] [Hide abstract] ABSTRACT: The purpose of this paper focuses on designing an intelligent, compact, reliable, and robust auxiliary vacuum brake system (VBS) with Kalman filter and self-diagnosis scheme. All of the circuit elements in the designed system are integrated into one programmable system-on-chip (PSoC) with entire computational algorithms implemented by software. In this system, three main goals are achieved: (a) Kalman filter and hysteresis controller algorithms are employed within PSoC chip by software to surpass the noises and disturbances from hostile surrounding in a vehicle. (b) Self-diagnosis scheme is employed to identify any breakdown element of the auxiliary vacuum brake system. (c) Power MOSFET is utilized to implement PWM pump control and compared with relay control. More accurate vacuum pressure control has been accomplished as well as power energy saving. In the end, a prototype has been built and tested to confirm all of the performances claimed above.
Chienkuo Technology UniversityTaiwan