Adaptive Sugeno Fuzzy Control: A Case Study

Abstract

This paper proposes an inverse fuzzy-model-based controller. The gradient-descent algorithm can be used on-line to form adaptive fuzzy controllers. This ability allows the controller to be used in applications where the knowledge to control the process does not exist or the process is subject to changes in its dynamic characteristics. To demonstrate the feasibility of the method simulation and experimental control tests were evaluated in a non-linear level process, composed of mono-tank, which was submitted to reference change. The proposed adaptive Sugeno fuzzy logic controller is shown to be capable of compensating non-linear terms that affect the systems dynamics and providing better overall system performance than the optimal PI controller.