Browsing by Author "Lee, Bore-Kuen"

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Adaptive fuzzy control using PID-type learning algorithm
(2007-01-01)
Lee, Bore-Kuen
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Hsu, Chen-Fei
;
Chen, Guan-Ming
;
Lee, Tsu-Tian
;
電控工程研究所
This paper proposes a proportional-integral-derivative (PID)-learning-type adaptive fuzzy controller (AFC) for chaotic Duffing dynamic systems. The proposed PID-learning-type AFC is comprised of a fuzzy controller and a robust controller. The fuzzy controller is designed to mimic an ideal controller and the robust controller is designed to dispel the effect of the approximation error between the fuzzy controller and the ideal controller. All the control parameters are on-line tuned in the sense of Lyapunov theorem, thus the stability of the system can be guaranteed. Finally, a comparison between a conventional AFC and the proposed PID-learning-type AFC is presented. Simulation results verify that the proposed PID-learning-type AFC can achieve better tracking performance and faster tracking error convergence than the conventional AFC for chaotic Duffing dynamic systems.
Adaptive Two-Stage Fuzzy Temperature Control for an Electroheat System
(2009-03-01)
Wang, Chih-Hu
;
Lin, Chun-Hung
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Lee, Bore-Kuen
;
Liu, Chien-Nan Jimmy
;
Su, Chauchin
In this paper, we construct a simple adaptive two-stage fuzzy temperature tracking controller for a commercial electroheat system. Being not well isolated from the environment, it is hard to build an analytical model for the system due to heat convection caused by a fan for heat mixing in the chamber, heat leakage to the environment, variation of the environment temperature, and uncertain nonlinear heating dynamics. Also, as a commercial product by using cheap heater coils and without equipping a cooling system, this system usually has a bad transient response such as a long rise time, a large overshoot, and a long settling time. Moreover, temperature tracking at the steady-state phase is not easy to maintain due to heat interaction with the environment. Here, in the presence of the unknown system dynamics, we use a two-stage fuzzy controller to improve the transient response. Furthermore, a simple fine-tuning adaptive control scheme is proposed to overcome environmental influence and ensure tracking of the temperature setting. Simulation study and experimental results show good performance of the adaptive fuzzy temperature control system.
Estimation of loss coefficients of Nonlinear rubber using iterative H-infinity filter
(2006-01-01)
Chih-Hu Wang
;
Lee, Bore-Kuen
;
Wei-Hang Tseng
;
Chung-Hsi Fu
;
Chauchin Su
For automobile industry, rubber is widely used for noise isolation and vibration reduction. However, due to its distributed and nonlinear characteristics, it is hard to precisely estimate its characteristics such as the loss coefficient which is defined as the tangent of the phase delay between the fundamental components of the strain and the stress under sinusoidal driving. Moreover, even using a truncated finite-dimensional model, with rubber's nonlinearity, resonance of the testing mechanical system, and measurement noise, optimal estimation of the loss coefficient by using Kalman filter is not feasible in the presence of these uncertainties and non-Gaussian disturbances. Therefore, H-infinity filter is applied in this paper to robustly estimate the loss coefficient from the state-space perspective. As a state-space model for representing a sinusoidal signal has eigenvalues on the unit circle, the measured data is first processed by imposing a suitable exponential decay in order to ensure the stability of the H-infinity filter. Moreover, due to finite data length, an iterative H-infinity filter is developed to improve the accuracy of parameter estimates. At each iteration, estimation of disturbances by using the H-infinity filter is first performed by applying the previously estimated components of the desired signal. Then a robust estimation of the desired signal is made with respect to the measured signal which is subtracted by the estimated disturbance. Both simulation study and experimental test are conducted to verify the performance of the proposed iterative H. filter.
H-infinity output feedback control of stochastic T-S fuzzy model with state-dependent noise
(2008-01-01)
Ho, Shih-Ju
;
Wang, Chih-Hu
;
Lee, Bore-Kuen
;
Su, Chauchin
;
Liu, Chien-Nan Jimmy
Estimator which guarantee H-infinity robustness performance for the considered nonlinear stochastic systems can be obtained by solving bilinear matrix inequalities. Then, to solve the bilinear matrix inequalities, a two-stage method is adopted to separately obtain the controller gain matrices and the eatimator gain matrices by solving two sets of linear matrix inequalities. An example is given to verify the derived results.
Long-Range Prediction for Real.-Time MPEG Video Traffic: An H(infinity) Filter Approach
(2008-12-01)
Wang, Chih-Hu
;
Chen, Bor-Sen
;
Lee, Bore-Kuen
;
Lee, Tsu-Tian
;
Liu, Chien-Nan Jimmy
A novel prediction scheme is proposed for real-time MPEG video to predict the burst and long-range dependent traffic. The trend and periodic characteristics of MPEG video traffic are fully captured by a proposed stochastic state-space dynamic model. Then a recursive H. filtering algorithm is proposed to estimate traffic for long-range prediction. Simulation results based on real MPEG traffic data show that the proposed scheme has superior performance and lower complexity than some adaptive neural network methods, such as TDNN, NARX, and Elman neural networks.