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.
Della Penna, G., Intrigila, B., & Magazzeni, D. (2009). Evaluating fuzzy controller robustness using model checking. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp.303-311) [10.1007/978-3-642-02282-1_38].
Evaluating fuzzy controller robustness using model checking
INTRIGILA, BENEDETTO;
2009
Abstract
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.