Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/81990
Title: Enhanced Adaptive Fuzzy Control With Optimal Approximation Error Convergence
Authors: Pan, Yongping
Er, Meng Joo
Keywords: Asymptotically stable
Adaptive control
Issue Date: 2013
Source: Pan, Y., & Er, M. J. (2013). Enhanced Adaptive Fuzzy Control With Optimal Approximation Error Convergence. IEEE Transactions on Fuzzy Systems, 21(6), 1123-1132.
Series/Report no.: IEEE Transactions on Fuzzy Systems
Abstract: In this paper, an enhanced adaptive fuzzy control (AFC) strategy with guaranteed convergence of an optimal fuzzy approximation error (FAE) is presented for a class of uncertain nonlinear systems in the general Brunovsky form. Based on the fuzzy logic system (FLS) with variable universes of discourse, relaxed sufficient conditions that guarantee the optimal FAE being convergent are given, and the upper bound of the optimal FAE is obtained. The control singularity problem resulting from the unknown affine term is resolved by a novel fuzzy approximation equation, and the parameter adaptive law of the FLS is derived by the Lyapunov synthesis. By means of the optimal FAE bound result, it is proved that the closed-loop system achieves partially asymptotic stability under a certain selection of control parameters. The proposed approach retains all advantages of a previous similar approach under relaxed constraint conditions. Thus, it provides a more flexible solution to the AFC with optimal FAE convergence. Simulation studies have demonstrated high-precision tracking performance with smooth control input of the proposed approach.
URI: https://hdl.handle.net/10356/81990
http://hdl.handle.net/10220/41073
DOI: 10.1109/TFUZZ.2013.2244899
Schools: School of Electrical and Electronic Engineering 
Rights: © 2013 IEEE.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Journal Articles

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