Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/129721
Title: A neural network based method for solving discrete-time nonlinear output regulation problem in sampled-data systems
Authors: Wang, D. 
Huang, J.
Issue Date: 2004
Source: Wang, D., Huang, J. (2004). A neural network based method for solving discrete-time nonlinear output regulation problem in sampled-data systems. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 3174 : 59-64. ScholarBank@NUS Repository.
Abstract: Many of nonlinear control systems are sampled-data system, i.e. the continuous-time nonlinear plants are controlled by digital controllers. So it is important to investigate that if the solution of the discrete-time output regulation problem is effective to sampled-data nonlinear control systems. Recently a feedforward neural network based approach to solving the discrete regulator equations has been presented. This approach leads to an effective way to practically solve the discrete nonlinear output regulation problem. In this paper the approach is used to sampled-data nonlinear control system. The simulation of the sampled-data system shows that the control law designed by the proposed approach performs much better than the linear control law does. © Springer-Verlag 2004.
Source Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
URI: http://scholarbank.nus.edu.sg/handle/10635/129721
ISSN: 03029743
Appears in Collections:Staff Publications

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