Multivariable Process Control Using Decentralized Single Neural Controllers

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概要

• 論文の詳細を見る

• 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.

• 社団法人 化学工学会の論文

著者

• Chen Chyi-tsong

  Department Of Chemical Engineering Feng Chia University

• YEN Jia-Hwang

  Department of Chemical Engineering, Feng Chia University

• Chen Chyi-tsong

  Department Of Chemical Engineering

• Yen Jia-hwang

  Department Of Chemical Engineering Feng Chia University

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