Abstract
In this paper, an adaptive fuzzy state-feedback control scheme is proposed for a class of uncertain multi-input multioutput (MIMO) nonlinear systems. The fuzzy logic systems (FLS) are used to online approximate unknown nonlinear functions. To improve the parameter convergence as well as the tracking performances, an adaptation proportional-integral (PI) law is proposed. In the control design procedure and stability analysis, a matrix factorization lemma is exploited. The later consists to decompose the control gain matrix into a symmetric positive-definite matrix, a diagonal matrix with diagonal entries +1 or −1 and a unity upper triangular matrix. A Lyapunov approach is employed to simultaneously prove the asymptotic convergence of the tracking errors towards the origin and the boundedness of the adaptive fuzzy parameters. Finally, simulation results are provided to show the effectiveness of the proposed control scheme.
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