This paper presents a fuzzy controller and observer design for backward movement control of a trailer-truck A nonlinear dynamic model of the trailer-truck is represented by a Takagi-Sugeno fuzzy model. The concept of ...
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This paper presents a fuzzy controller and observer design for backward movement control of a trailer-truck A nonlinear dynamic model of the trailer-truck is represented by a Takagi-Sugeno fuzzy model. The concept of parallel distributed compensation is employed to design a fuzzy controller and a fuzzy observer from the Takagi-Sugeno fuzzy model of the trailer-truck. Stability conditions of the fuzzy control system are derived, using the Lyapunov approach. It is shown that the stability conditions are characterized in terms of linear matrix inequalities (LMIs). Stability of the overall fuzzy control system, including a fuzzy controller and a fuzzy observer is guaranteed by using a convex optimization technique based on LMIs. Simulation and experimental results show that the fuzzy controller and the fuzzy observer effectively achieve backward movement control of the trailer-truck. (C) 1997 Published by Elsevier Science Ltd. All rights reserved.
This paper presents new stability conditions and LMI (linear matrix inequality) based designs for both continuous and discrete fuzzy control systems. First, Takagi and Sugeno's fuzzy models and some stability resu...
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ISBN:
(纸本)0780335910
This paper presents new stability conditions and LMI (linear matrix inequality) based designs for both continuous and discrete fuzzy control systems. First, Takagi and Sugeno's fuzzy models and some stability results are recalled. To design fuzzy control systems, nonlinear systems are represented by Takagi-Sugeno fuzzy models. The concept of parallel distributed compensation is employed to design fuzzy controllers from the Takagi-Sugeno fuzzy models. New stability conditions are obtained by relaxing the stability conditions derived in previous papers. The stability analysis of the feedback system is reduced to a problem of finding a common Lyapunov function for a set of linear matrix inequalities. Convex optimization techniques involving LMIs are utilized to find a common Lyapunov function. A procedure to design the fuzzy controller is constructed using the parallel distributed compensation and the relaxed stability conditions. Some stability issues are remarked. A simple example demonstrates the effects of the derived stability conditions.
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