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Model reference adaptive control for multi-input multi-output nonlinear systems using neural networks

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3 Author(s)
Jiunshian Phuah ; Graduate Sch. of Sci. & Tech., Chiba Univ., Japan ; Jianming Lu ; Yahagi, T.

This paper presents a method of MRAC (model reference adaptive control) for multi-input multi-output (MIMO) nonlinear systems using NNs (neural networks). The control input is given by the sum of 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.

Published in:

Advanced Intelligent Mechatronics, 2003. AIM 2003. Proceedings. 2003 IEEE/ASME International Conference on  (Volume:1 )

Date of Conference:

20-24 July 2003