JOURNAL OF CHEMICAL ENGINEERING OF JAPAN | |
Multivariable Process Control Using Decentralized Single Neural Controllers | |
Jia-Hwang Yen1  Chyi-Tsong Chen1  | |
[1] Department of Chemical Engineering, Feng Chia University | |
关键词: Multivariable Process Control; Decentralized Control; Learning Control; Single Neural Controller; Parameter Tuning Algorithm; Static Decoupling; | |
DOI : 10.1252/jcej.31.14 | |
来源: Maruzen Company Ltd | |
【 摘 要 】
References(21)Cited-By(4)This paper develops a learning-type multi-loop control system for interacting multi-input/multi-output industrial process systems. The recently developed single neural controller (SNC) is adopted as the decentralized controller. With a simple parameter tuning algorithm, the SNC in each loop is able to learn to control a changing process by merely observing the process output error in the same loop. To circumvent loop interactions, static decouplers are incorporated in the presented scheme. The only a priori knowledge of the controlled plant is the process steady state gains, which can be easily obtained from open-loop test. Extensive comparisons with decentralized PI controllers were performed. Simulation results show that the presented decentralized nonlinear control strategy appears to be a simple and promising approach to interacting multivariable process control.
【 授权许可】
Unknown
【 预 览 】
Files | Size | Format | View |
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RO201912080694357ZK.pdf | 19KB | download |