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A hybrid adaptive output-feedback fuzzy decentralized control methodology is introduced for a class of large-scale nonlinear systems. The proposed controller has a primary-auxiliary control structure, where both directing an adaptive approaches is employed for the primary control part aiming to maintain the closed-loop stability, whilst in the auxiliary part a sliding-mode controller is designed to compensate for the interactions among subsystems and a H∞ -controller is designed to attenuate the fuzzy approximation errors. It turns out that this hybrid adaptive fuzzy decentralized controller can guarantee the stability of the closed-loop system and also achieve the H∞ -tracking performance. When used with an observer, the proposed approach can work for processes with unknown states, which is special feature unique to other existing adaptive fuzzy control methodologies. Simulation results confirm the effectiveness of the proposed control methodology.
Machine Learning and Cybernetics, 2003 International Conference on (Volume:2 )
Date of Conference: 2-5 Nov. 2003