کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
396104 666204 2007 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Robust adaptive critic control of nonlinear systems using fuzzy basis function networks: An LMI approach
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Robust adaptive critic control of nonlinear systems using fuzzy basis function networks: An LMI approach
چکیده انگلیسی

This paper proposes an adaptive critic tracking control design for a class of nonlinear systems using fuzzy basis function networks (FBFNs). The key component of the adaptive critic controller is the FBFN, which implements an associative learning network (ALN) to approximate unknown nonlinear system functions, and an adaptive critic network (ACN) to generate the internal reinforcement learning signal to tune the ALN. Another important component, the reinforcement learning signal generator, requires the solution of a linear matrix inequality (LMI), which should also be satisfied to ensure stability. Furthermore, the robust control technique can easily reject the effects of the approximation errors of the FBFN and external disturbances. Unlike traditional adaptive critic controllers that learn from trial-and-error interactions, the proposed on-line tuning algorithm for ALN and ACN is derived from Lyapunov theory, thereby significantly shortening the learning time. Simulation results of a cart–pole system demonstrate the effectiveness of the proposed FBFN-based adaptive critic controller.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Information Sciences - Volume 177, Issue 22, 15 November 2007, Pages 4934–4946
نویسندگان
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