Title: DSC approach to robust adaptive NN tracking control for a class of MIMO systems

Authors: Tieshan Li, Wei Li, Weilin Luo

Addresses: Navigation College, Dalian Maritime University, 1 Linghai Road, Dalian, 116026, China; School of Naval Architecture, Ocean and Civil Engineering (NAOCE), Shanghai Jiao Tong University, 800 Dongcuan Road, Shanghai 200240, China. ' Navigation College, Dalian Maritime University, 1 Linghai Road, Dalian, 116026, China. ' School of Naval Architecture, Ocean and Civil Engineering (NAOCE), Shanghai Jiao Tong University, 800 Dongcuan Road, Shanghai 200240, China

Abstract: A robust adaptive neural tracking controller is proposed for a class of MIMO non-linear systems with strongly coupled interconnections. With the help of RBF neural networks (NN) as approximator, a unified and systematic procedure is developed by fusion of |dynamic surface control (DSC)| with |minimal learning parameters| algorithm. As a result, both problems of |explosion of complexity| and |curse of dimension| are solved synchronously, especially, the number of updated parameters for each subsystem is reduced to two, which can reduce the computational burden to an extreme extent, consequently ease the implementation of the algorithm. Additionally, the possible controller singularity problem can be removed and the stability of the closed-loop system is guaranteed. Simulation results validate the effectiveness of the proposed scheme.

Keywords: adaptive control; RBF neural networks; NNs; dynamic surface control; DSC; minimal learning parameters; robust control; tracking controllers; MIMO nonlinear systems; stability; simulation.

DOI: 10.1504/IJMIC.2010.035274

International Journal of Modelling, Identification and Control, 2010 Vol.11 No.1/2, pp.5 - 14

Published online: 20 Sep 2010 *

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