Evaluating fuzzy controller robustness using model checking

Fuzzy control is well known as a powerful technique for designing and realizing controllers. However, statistical evidence for their correct behavior may be not enough, even when it is based on a large number of samplings. Therefore, much work is being done to provide a systematic verification of fuzzy controllers and to asses their robustness, that is the ability of a controller to maintain good performance even in the presence of significant disturbances or parameter variations. In the present paper, we introduce a model checking based methodology for the fuzzy controller robustness analysis, that can be applied on plant-controller pairs in a nearly automatic way, giving higher precision results than other approaches, such as cell mapping. We support our conclusions with a case study that compares two different fuzzy controllers for the inverted pendulum on a cart problem. © 2009 Springer Berlin Heidelberg.