關鍵字查詢 | 類別:期刊論文 | | 關鍵字:Adaptive dynamic RBF neural controller design for a class of nonlinear systems

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序號 學年期 教師動態
1 100/1 電機系 許駿飛 教授 期刊論文 發佈 Adaptive dynamic RBF neural controller design for a class of nonlinear systems , [100-1] :Adaptive dynamic RBF neural controller design for a class of nonlinear systems期刊論文Adaptive dynamic RBF neural controller design for a class of nonlinear systemsHsu, Chun-Fei淡江大學電機工程學系Adaptive control;Neural control;Lyapunov stability theorem;DC motor;Chaotic systemAmsterdam: Elsevier BVApplied Soft Computing 11(8), pp.4607–4613In this paper, an adaptive DRBF neural control (ADNC) system which is composed of a neural controller and a smooth compensator is proposed. The neural controller utilizes a dynamic radial basis function (DRBF) network to online mimic an ideal controller and the smooth compensator is designed to eliminate the effect of the approximation error between the ideal controller and neural controller. The DRBF network can self-organizing its network structure. All the controller parameters of the proposed ADNC system are online tuned in the Lyapunov sense, thus the stability analytic shows the system output can exponentially converge to a small neighborhood of the traject
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