Fuzzy model based predictive control and comparison with other nonlinear MBPC algorithms

In the paper a comparison of different nonlinear model-based predictive control algorithms is presented as a case study for a continuous stirred reactor. The focus is given to the fuzzy predictive control approach which is compared to Wiener based model predictive control and nonlinear model predictive control based on optimization. It has been shown that fuzzy predictive control law which is given in analytical form gives very promising results in comparison to other two approaches which are both based on optimization. All the proposed approaches are potentially interesting in the case of batch reactors, heat-exchangers, furnaces and all the processes with strong nonlinear dynamics.

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