Browsing by Author "Chin, HI"

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Gain-phase margin analysis of dynamic fuzzy control systems
(2004-10-01)
Perng, JW
;
Wu, BF
;
Chin, HI
;
Lee, TT
;
電控工程研究所
In this paper, we apply some effective methods, including the gain-phase margin tester, describing function and parameter plane, to predict the limit cycles of dynamic fuzzy control systems with adjustable parameters. Both continuous-time and sampled-data fuzzy control systems are considered. In general, fuzzy control systems are nonlinear. By use of the classical method of describing functions, the dynamic fuzzy controller may be linearized first. According to the stability equations and parameter plane methods, the stability of the equivalent linearized system with adjustable parameters is then analyzed. In addition, a simple approach is also proposed to determine the gain margin and phase margin which limit cycles can occur for robustness. Two examples of continuous-time fuzzy control systems with and without nonlinearity are presented to demonstrate the design procedure. Finally, this approach is also extended to a sampled-data fuzzy control system.
Limit cycle analysis of nonlinear sampled-data systems by gain-phase margin approach
(2005-03-01)
Wu, BF
;
Perng, JW
;
Chin, HI
;
電控工程研究所
;
Institute of Electrical and Control Engineering
This work analyzes the limit cycle phenomena of nonlinear sampled-data systems by applying the methods of gain-phase margin testing, the M-locus and the parameter plane. First, a sampled-data control system with nonlinear elements is linearized by the classical method of describing functions. The stability of the equivalent linearized system is then analyzed using the stability equations and the parameter plane method, with adjustable parameters. After the gain-phase margin tester has been added to the forward open-loop system, exactly how the gain-phase margin and the characteristics of the limit cycle are related can be elicited by determining the intersections of the M-locus and the constant gain and phase boundaries. A concise method is presented to solve this problem. The minimum gain-phase margin of the nonlinear sampled-data system at which a limit cycle can occur is investigated. This work indicates that the procedure can be easily extended to analyze the limit cycles of a sampled-data system from a continuous-data system cases considered in the literature. Finally, a sampled-data system with multiple nonlinearities is illustrated to verify the validity of the procedure. (C) 2004 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
Limit cycle analysis of uncertain fuzzy vehicle control systems
(2005)
Perng, JW
;
Wu, BF
;
Chin, HI
;
Lee, TT
;
電控工程研究所
In this paper, some useful frequency domain methods including describing function, parameter space and Kharitonov approach are applied to analyze the stability of a fuzzy vehicle control system for limit cycle prediction. A systematic procedure is proposed to solve this problem. In general, fuzzy control systems are nonlinear systems. The fuzzy controller can be linearized by the use of classical describing function firstly. By doing so, it is feasible to treat the stability problem of fuzzy control systems as linear one. In order to consider the robustness of the fuzzy vehicle control system, parameter space method and Kharitonov approach are then employed for plotting the stability boundaries. Furthermore, the effect of transport delay is also addressed. Much information of limit cycles can be obtained by this approach. Our work shows that the limit cycles caused by a fuzzy controller can be easily suppressed if the system parameters are chosen carefully.
Stability analysis of a robust fuzzy vehicle steering control system
(2005)
Perng, JW
;
Chin, HI
;
Wu, BF
;
Lee, TT
;
電控工程研究所
The main purpose of this paper is to analyze the stability for a fuzzy vehicle steering control system. In general, fuzzy control system is a nonlinear control system. Therefore, the fuzzy controller may be linearized by the use of describing function first; After then, the traditional frequency domain method i.e. parameter plane, is then applied to determine the condition of stability when the system has perturbed or adjustable parameters. A systematic procedure is proposed to solve this problem. The stability problem under the effects of plant parameters and control factors are both considered here. Furthermore, the effect of transport delay is also addressed. The limit cycles provided by a static fuzzy controller can be easily suppressed if the system parameters are chosen properly. Simulation results show the efficiency of our approach.