Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/69167
Title: Adaptive control of partially known nonlinear multivariable systems using neural networks
Authors: Ge, S.S. 
Wang, C.
Tan, Y.H.
Issue Date: 2001
Source: Ge, S.S.,Wang, C.,Tan, Y.H. (2001). Adaptive control of partially known nonlinear multivariable systems using neural networks. IEEE International Symposium on Intelligent Control - Proceedings : 292-297. ScholarBank@NUS Repository.
Abstract: In this paper, an adaptive neural control scheme is proposed for a class of partially known interconnected MIMe nonlinear systems in block-triangular form, with both unknown nonlinearities and parametric uncertainties. The MIMe systems is composed of interconnected subsystems. The system state interconnections make it difficult to conclude the stability of the whole system by stability analysis of individual subsystem separately. By exploiting the block-triangular structure properties, we first design for each subsystem a full state feedback controller, and then conclude the stability of all the state variables in a nested iterative manner. Semi-global uniform ultimate boundedness of all the signals in the closed-loop of MIMO nonlinear systems is guaranteed. The outputs of the systems are proven to converge to small neighbourhoods of the desired trajectories. The control performance of the closed-loop system is guaranteed by suitably choosing the design parameters.
Source Title: IEEE International Symposium on Intelligent Control - Proceedings
URI: http://scholarbank.nus.edu.sg/handle/10635/69167
Appears in Collections:Staff Publications

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