Browsing by Author "Chiang, HH"

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A bifurcation study of vehicle's steering dynamics
(2005)
Liaw, DC
;
Chiang, HH
;
Lee, TT
;
電控工程研究所
;
Institute of Electrical and Control Engineering
Issues of stability and bifurcation phenomena in vehicle's steering dynamics are presented. Based on the assumption of constant driving speed, a second order nonlinear lateral dynamical model is obtained. Local stability and existence conditions for saddle node bifurcation appearing in vehicle dynamics with respect to the variation of the front wheel steering angle are then derived via system linearization and local bifurcation analysis. Bifurcation phenomena occurring in nonlinear vehicle lateral dynamics might result in spin and/or system instability. Perturbation method is employed to solve for an approximation of system equilibrium near the zero value of the front wheel steering angle, which reveals the relationship between sideslip angle and the applied front wheel angle. Numerical study of a simple example verifies the theoretical analysis.
Application of fuzzy sets theory in process data filtering
(2003)
Chiang, HH
;
Wu, SJ
;
Lee, TT
;
電控工程研究所
;
Institute of Electrical and Control Engineering
introduced and applied to the problems of signal restoration. A fuzzy approach for system identification and state estimation is developed. The estimated values obtained from the fuzzy model are in the form of fuzzy numbers which present the possibility of the system structure. Both L-R and symmetric triangular type membership functions are employed to derive the fuzzy-data based estimator (FBE). Illustrative examples with white and color noise are provided to demonstrate the applicability and effectiveness of the developed FBE. Comparisons between the FBE and various modified Kalman filter are also included.
Fuzzy approach for disturbance reduction
(2003)
Chiang, HH
;
Wu, SJ
;
Lee, TT
;
電控工程研究所
;
Institute of Electrical and Control Engineering
The basic principles of the fuzzy set theory are applied to the signal restoration problems. The estimated values obtained from the fuzzy model are in the form of fuzzy numbers which present the possibility of the system structure. Both L-R and symmetric triangular type membership functions are employed to derive the fuzzy disturbance reduction. The quarter-car semi-active suspension system with unknown disturbance caused by roughness of road is provided to demonstrate the applicability and effectiveness of the proposed fuzzy algorithm in disturbance reduction problem.
Neural-network-based optimal fuzzy controller design for nonlinear systems
(2005-09-01)
Wu, SJ
;
Chiang, HH
;
Lin, HT
;
Lee, TT
;
電控工程研究所
A neural-learning fuzzy technique is proposed for T-S fuzzy-model identification of model-free physical systems. Further, an algorithm with a defined modelling index is proposed to integrate and to guarantee that the proposed neural-based optimal fuzzy controller can stabilize physical systems; the modelling index is defined to denote the modelling-error evolution, and to ensure that the training data for neural learning can describe the physical system behavior very well; the algorithm, which integrates the neural-based fuzzy modelling and optimal fuzzy controlling process, can implement off-line modelling and on-line optimal control for model-free physical systems. The neural-fuzzy inference network is a self-organizing inference system to learn fuzzy membership functions and fuzzy-subsystems' parameters as data feeding in. Based on the generated T-S fuzzy models for the continuous mass-spring-damper system and Chua's chaotic circuit, discrete-time model car system and articulated vehicle, their corresponding fuzzy controllers are formulated from both local-concept and global-concept fuzzy approach, respectively. The simulation results demonstrate the performance of the proposed neural-based fuzzy modelling technique and of the integrated algorithm of neural-based optimal fuzzy control structure. (c) 2005 Elsevier B.V. All rights reserved.