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• W2058512397 startingPage "2266" @default.
• W2058512397 abstract "This paper proposes a robust adaptive fuzzy PID control scheme augmented with a supervisory controller for unknown systems. In this scheme, a generalized fuzzy model is used to describe a class of unknown systems. The control strategy allows each part of the control law, i.e., a supervisory controller, a compensator, and an adaptive fuzzy PID controller, to be designed incrementally according to different guidelines. The supervisory controller in the outer loop aims at enhancing system robustness in the face of extra disturbances, variation in system parameters, and parameter drift in the adaptation law. Furthermore, an H∞ control design method using the fuzzy Lyapunov function is presented for the design of the initial control gains that guarantees transient performance at the start of closed-loop control, which is generally overlooked in many adaptive control systems. This design of the initial control gains is a compound search strategy called conditional linear matrix inequality (CLMI) approach with IROA (Improved random optimal algorithm), it leads to less complex designs than a standard LMI method by fuzzy Lyapunov function. Numerical studies of the tracking control of an uncertain inverted pendulum system demonstrate the effectiveness of the control strategy. From results of this simulation, the generalized fuzzy model reduces the rule number of T-S fuzzy model indeed." @default.
• W2058512397 created "2016-06-24" @default.
• W2058512397 creator A5068230274 @default.
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• W2058512397 date "2009-01-01" @default.
• W2058512397 modified "2023-09-25" @default.
• W2058512397 title "Adaptive Tracker Design with Identifier for Pendulum System by Conditional LMI Method and IROA" @default.
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• W2058512397 doi "https://doi.org/10.1587/transfun.e92.a.2266" @default.
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