A simplified adaptive interval Type-2 fuzzy control in practical industrial application

Adaptive Type-2 fuzzy control possesses control performance better than the traditional adaptive fuzzy control. However, heavy computation burden obviously blocks the utilization of adaptive Type-2 fuzzy control in industrial application. By adopting novel piecewise fuzzy sets and center-average type-reduction, a simplified adaptive interval Type-2 fuzzy controller involving less computation is developed for practical industrial application. In the proposed controller, the inputs are divided into several subintervals and then two piecewise fuzzy sets are used for each subinterval. With the manner of piecewise fuzzy sets and a novel fuzzy rules inference engine, only part of fuzzy rules are simultaneously activated in one control loop, which exponentially decreases the computation and makes the controller appropriate in industrial application. The simulation and experimental study, involving the popular magnetic levitation platform, shows the predicted system with theoretical stability and good tracking performance. The analysis indicates that there is far less computation of the proposed controller than the traditional adaptive interval Type-2 fuzzy controller, especially when the number of fuzzy rules and fuzzy sets is large, and the controller still maintains good control performance as the traditional one.