Optimization issues in predictive control with fuzzy objective functions

Fuzzy predictive control integrates conventional model-based predictive con trol with techniques from fuzzy multicriteria decision making. The informat ion regarding the fuzzy criteria of the control problem is combined by usin g a decision function from the fuzzy set-theory. The use of fuzzy criteria in the cost function leads usually to a non-convex optimization problem, wh ich is numerically complex. The numeric optimization problem becomes more t ractable by discretizing the control actions, limiting the search of the op timal solution to this space. This paper extends the application of the bra nch-and-bound optimization technique to predictive control problems with fu zzy cost functions. This approach can reduce significantly the search time, allowing the application of fuzzy predictive control to a broader class of systems, and to real-time control problems. Simulation and real-time resul ts of temperature control in a fan-coil unit show the applicability of the approach. (C) 2000 John Wiley & Sons, Inc.