Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/69956
Title: Direct Adaptive Control for a Class of Multi-input and Multi-output Nonlinear Systems Using Neural Networks
Authors: Ge, S.S. 
Li, G.Y.
Xi, N.
Issue Date: 2003
Source: Ge, S.S.,Li, G.Y.,Xi, N. (2003). Direct Adaptive Control for a Class of Multi-input and Multi-output Nonlinear Systems Using Neural Networks. Proceedings of the IEEE Conference on Decision and Control 3 : 2716-2721. ScholarBank@NUS Repository.
Abstract: In this paper, direct adaptive neural network control is studied for a class of multi-input and multi-output (MIMO) nonlinear systems based on input-output model with unknown inter connections between subsystems. The proposed adaptive algorithm is very simple and easy to implement. By finding a unitary orthogonal matrix to tune the NN weights, the closed-loop system is proved to be semi-globally uniformly ultimately bounded (SGUUB). The control performance of the closed-loop system is guaranteed by suitably choosing the design parameters.
Source Title: Proceedings of the IEEE Conference on Decision and Control
URI: http://scholarbank.nus.edu.sg/handle/10635/69956
ISSN: 01912216
Appears in Collections:Staff Publications

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