Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/44548
標題: Stochastic model reference predictive temperature control with integral action for an industrial oil-cooling process
作者: Tsai, C.C.
蔡清池
Lin, S.C.
Wang, T.Y.
Teng, F.J.
關鍵字: Adaptive control;Oil-cooling process;Generalized predictive control;(GPC);Temperature control;Variable frequency;injection-molding process;reactors;tracking;machine;barrel
Project: Control Engineering Practice
期刊/報告no:: Control Engineering Practice, Volume 17, Issue 2, Page(s) 302-310.
摘要: 
This paper presents a stochastic model reference predictive control (SMRPC) approach to achieving accurate temperature control for an industrial oil-cooling process, which is experimentally modeled as a simple first-order system model with given long time delay. Based on this model, the stochastic model reference predictive controller with control weighting and integral action is derived based on the minimization of an expected generalized predictive control (GPC) performance criteria. A real-time adaptive SMRPC algorithm is proposed and then implemented into a stand-alone digital signal processor (DSP). Experimental results show that the proposed control method is capable of giving accurate and satisfactory control performance under set-point changes, fixed load and load changes. (C) 2008 Elsevier Ltd. All rights reserved.
URI: http://hdl.handle.net/11455/44548
ISSN: 0967-0661
DOI: 10.1016/j.conengprac.2008.07.009
Appears in Collections:電機工程學系所

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