Detail Robust Sliding-Mode Control for Nonlinear Flexible Arm Via Neural Network   Oleh:  Wai, R.J. ; Chen, P.C. ; Lee, M.C. Jenis: Article from Article Dalam koleksi: Final Program and Book of Abstracts: The 4th Asian Control Conference, September 25-27, 2002 (Sep. 2002), page 996-1001. Topik: Nonlinear; Flexible Arm; Neural Network Fulltext: AC021388.PDF (331.13KB) Isi artikel This study addresses the design and properties of a slidingmode neural-network control (SMNNC) system for a nonlinear flexible arm that is driven by a permanent magnet (PM) synchronous servo motor. First, the dynamic model of a flexible arm system with a tip mass is introduced. Then, a SMNNC system is proposed to control the motor-mechanism coupling system for periodic motion. n the SMNNC system a neural network (NN) controller is used to learn an equivalent control law as in the traditional sliding-mode control, and a robust controller is designed to ensure the near total sliding motion through the entire state trajectory without a reaching phase. Moreover, a simple adaptive algorithm is proposed to adjust the uncertain bound in the robust controller avoiding the chattering phenomena. The effectiveness of the proposed control scheme is verified by both the numerical and experimental results. Opini Anda Klik untuk menuliskan opini Anda tentang koleksi ini! Kembali

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