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pH control: handling nonlinearity and deadtime with fuzzy relational model-based control

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2 Author(s)
Sing, C.H. ; Dept. of Chem. & Process. Eng., Strathclyde Univ., Glasgow, UK ; Postlethwaite, B.

The application of fuzzy logic to the design of nonlinear controllers has become increasingly popular in recent years. Most of the developments have been in controllers of the rule-based type. An alternative approach, and one which reflects trends in conventional control, is to use fuzzy logic to build a process model, and then to incorporate this into a standard model-based controller scheme. The paper proposes the application of fuzzy relational models (FRMs) for the nonlinear control of a pH process. The pH in both a simulated and a laboratory continuously stirred tank reactor (CSTR) was controlled by a model predictive controller (MPG), incorporating a fuzzy model created using a recently developed method of FRM identification. The controller performance is compared with that of a fuzzy rule-based controller, that of a PID controller and that of a linear MPG. The comparison shows the superiority of fuzzy relational model-based control (FRMBC) for highly nonlinear processes. The suitability of the FRMBC for real-world applications is demonstrated by its control performance on a laboratory-scale plant

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Control Theory and Applications, IEE Proceedings -  (Volume:144 ,  Issue: 3 )