Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/72657
Title: Gain scheduling control of nonlinear plant using RBF neural network
Authors: Chai, Joo-Siong 
Tan, Shaohua 
Hang, Chang-Chieh 
Issue Date: 1996
Source: Chai, Joo-Siong,Tan, Shaohua,Hang, Chang-Chieh (1996). Gain scheduling control of nonlinear plant using RBF neural network. IEEE International Symposium on Intelligent Control - Proceedings : 502-507. ScholarBank@NUS Repository.
Abstract: In this paper, an on-line approach to gain scheduling control of a type of nonlinear plant is proposed. The method consists of a partitioning algorithm to partition the plant's operating space into several regions, a mechanism that designs a linear controller for each region, and a radial basis function neural network (RBFN) for on-line interpolation of the controller parameters among the different regions. The method is described in detail, and is studied analytically in computer simulation on gain scheduled PI control of a nonlinear plant, which shows encouraging performance.
Source Title: IEEE International Symposium on Intelligent Control - Proceedings
URI: http://scholarbank.nus.edu.sg/handle/10635/72657
Appears in Collections:Staff Publications

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