Nonlinear Model Predictive Control Based on Multi-linear Models of an Unstable Chemical Reactor

眾所周知，將程序操作在不穩定點的條件上是很具挑戰性的控制問題。本研究藉由空間距離權重的概念，提出簡便且有效的方法，結合一組局部線性化模式成為一整體的模式，可準確地代表線性程序。為求減輕計算負荷，在模式預測控制架構中，上述之多重模式即可作為預測方程式來計算程序未來的輸出值。同時，本研究提出一些參數調諧策略，確保此預測控制系統具有低超越及良好的韌性。最後，將所發展的多重模式預測控制技術應用於典型非線性不穩定的化學反應製程控制問題上，以證實其效能。

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並列摘要

It is well known that operating a process under unstable conditions is a challenging control problem. In this article, by use of basic concepts of the weighted space distance, a set of locally linearized models is simply and effectively combined into a global description of a nonlinear plant. To reduce the computational load, these multiple linear models are then used as prediction equations in an MPC framework. Simultaneously, some parameter tuning strategies are presented to guarantee low overshoot and good robustness for the predictive control system. The effectiveness of the proposed multiple linear model predictive control with state estimation is demonstrated through its application to the exothermic chemical reactor, which is a typical nonlinear unstable process.

並列關鍵字

Nonlinear model predictive control ； Multiple linear model ； State estimation ； Weighted space distance ； Unstable process

國際替代計量

Nonlinear Model Predictive Control Based on Multi-linear Models of an Unstable Chemical Reactor

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