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|Title:||Reference governor control of constrained feedback systems using neural networks||Authors:||Jahagirdar, H.
Ang Jr., M.H.
|Issue Date:||2002||Citation:||Jahagirdar, H.,Keerthi, S.S.,Ang Jr., M.H. (2002). Reference governor control of constrained feedback systems using neural networks. IEEE International Symposium on Intelligent Control - Proceedings : 223-227. ScholarBank@NUS Repository.||Abstract:||A neural network approach to reference governor control of systems with constraints on state and control variables is discussed. A feed-forward neural network architecture is used to define safety sets in a constrained system state-space. Results presented here include the description of a neural reference governor algorithm and its application to linear and nonlinear control systems. The objective is to demonstrate the feasibility of such a design as an alternative to the Lyapunov function approach to the control of constrained systems.||Source Title:||IEEE International Symposium on Intelligent Control - Proceedings||URI:||http://scholarbank.nus.edu.sg/handle/10635/73804|
|Appears in Collections:||Staff Publications|
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