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|Title:||Observer-based direct adaptive fuzzy-neural control for nonaffine nonlinear systems|
|Publisher:||IEEE Computational Intelligence Society|
|Abstract:||In this paper, an observer-based direct adaptive fuzzy-neural control scheme is presented for nonafﬁne nonlinear systems in the presence of unknown structure of nonlinearities. A direct adaptive fuzzy-neural controller and a class of generalized nonlinear systems, which are called nonafﬁne nonlinear systems, are instead of the indirect one and afﬁne nonlinear systems given by Leu et al. By using implicit function theorem and Taylor series expansion, the observer-based control law and the weight update law of the fuzzy-neural controller are derived for the nonafﬁne nonlinear systems. Based on strictly-positive-real (SPR) Lyapunov theory, the stability of the closed-loop system can be veriﬁed. Moreover, the overall adaptive scheme guarantees that all signals involved are bounded and the output of the closed-loop system will asymptotically track the desired output trajectory. To demonstrate the effectiveness of the proposed method, simulation results are illustrated in this paper|
|Appears in Collections:||教師著作|
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