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A method of designing a nonlinear predictive controller based on relational fuzzy model is presented. The fuzzy model is incorporated as a predictor in a nonlinear model - based predictive controller, using internal model control scheme to compensate disturbances and modeling errors. A non-convex optimization problem must be solved at each sampling period. The algorithm is applied to temperature control in a heat exchanger.
Automation, Quality and Testing, Robotics, 2008. AQTR 2008. IEEE International Conference on (Volume:2 )
Date of Conference: 22-25 May 2008