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A Method of Model Reference Adaptive Control for MIMO Nonlinear Systems Using Neural Networks
Jianming LU Jiunshian PHUAH Takashi YAHAGI
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Publication Date: 2001/08/01
Print ISSN: 0916-8508
Type of Manuscript: Special Section PAPER (Special Section on Digital Signal Processing)
Category: Nonlinear Signal Processing
MRAC, MIMO nonlinear system, neural network,
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This paper presents a method of MRAC (model reference adaptive control) for MIMO (multi-input multi-output) nonlinear systems using NNs (neural networks). The control input is given by the sum of the output of a model reference adaptive controller and the output of the NN (neural network). The NN is used to compensate the nonlinearity of plant dynamics that is not taken into consideration in the usual MRAC. The role of the NN is to construct a linearized model by minimizing the output error caused by nonlinearities in the control systems.