Please use this identifier to cite or link to this item: https://doi.org/10.1252/jcej.06WE127
Title: Adaptive single-neuron controller design for nonlinear process control
Authors: Cheng, C.
Chiu, M.-S. 
Keywords: Adaptive control
Just-in-time learning
PID controller
Issue Date: 2008
Source: Cheng, C., Chiu, M.-S. (2008). Adaptive single-neuron controller design for nonlinear process control. Journal of Chemical Engineering of Japan 41 (8) : 785-795. ScholarBank@NUS Repository. https://doi.org/10.1252/jcej.06WE127
Abstract: In this paper, a new adaptive single-neuron (ASN) controller is proposed based on the just-in-time learning (JITL) technology for nonlinear process control. To mimic the traditional PID controller, a single neuron is employed in the proposed controller design strategy. Incorporated with the neural network's learning ability, the proposed controller can control the process adaptively through the updating of its parameters by the adaptive learning algorithm developed and the information provided from the JITL. Compared with the neural network based PID controller designs previously developed, ASN controller is more amenable to on-line implementation. Simulation results are presented to illustrate the proposed method and a comparison with its conventional counterparts is made. Copyright © 2008 The Society of Chemical Engineers, Japan.
Source Title: Journal of Chemical Engineering of Japan
URI: http://scholarbank.nus.edu.sg/handle/10635/63439
ISSN: 00219592
DOI: 10.1252/jcej.06WE127
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