Predictive control using fuzzy models — Comparative study

Fuzzy control and predictive control techniques are two modem control strategies that have been accepted by the industry to solve complex problems. Everyday the industry demands control strategies that can deliver better performance for several operating points and these requirements have motivated the development of the theory of Nonlinear Model Predictive Control. This type of controllers can be implemented using fuzzy models. The present paper presents 4 algorithms to construct the controllers. The comparison between the algorithms includes complexity, computational load, model representation, quality of the solution. The controllers are compared using a model of a chemical process (Continuous Stirred Tank Reactor).

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