Release Time:2022-06-30  Hits:

Date of Publication: 2011-01-01

Journal: 控制与决策

Volume: 26

Issue: 6

Page Number: 916-920

ISSN: 1001-0920

Abstract: This paper presents a design scheme of least squares support vector machines （LS-SVM） based direct adaptive H∞ output feedback control for a class of nonlinear uncertain systems whose state variables are not available. Firstly, a class of error observer is designed to estimate the system states indirectly. Then the adaptive outout feedback controller is constructed by using LS-SVM, and an on-line learning rule for the weigh vector and bias is derived. H∞ control is used to attentuate the effect on the tracking error caused by LS-SVM approximation errors and external disturbance. Lyapunov theory is used to prove the stability of the close-loop system. Finally, numerical simulations show the feasibility and effectiveness of the proposed method.

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