Synthesizing Fuzzy Based Model Predictive Controller

Ebrahim A. Mattar, K. Mutib
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Abstract

Abstract — The article presents a Fuzzy structure for a Model Predictive Control (MPC) system. MPC theorem has earlier been incorporated with fuzzy models. Such an integration provides controller design methods for an MPC control system. The paper concentrates on aspects of fuzzy based MPC for multivariable systems. Mathematical formulation of linearized MPC is utilized to introduce the concept of fuzzy based MPC scheme, then fuzzy MPC is constructed based on a modeled pH reactor. Results have shown that although the plant was nonlinear in characteristics, but still the employed Neuro-fuzzy system was able to model the plant into three different linear regions.
基于模糊模型的综合预测控制器
摘要:本文提出了模型预测控制(MPC)系统的模糊结构。MPC定理早先已被纳入模糊模型。这种集成为MPC控制系统提供了控制器设计方法。本文主要研究了多变量系统的模糊MPC问题。利用线性化MPC的数学公式,引入模糊MPC方案的概念,并以pH反应器模型为基础构建模糊MPC方案。结果表明,尽管植物具有非线性特征,但所采用的神经模糊系统仍然能够将植物建模为三个不同的线性区域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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