Fuzzy Stochastic Automata for Reactive Learning and Hybrid Control

Authors:
Gerasimos G. Rigatos
Affiliations:
-
Venue:
SETN '02 Proceedings of the Second Hellenic Conference on AI: Methods and Applications of Artificial Intelligence
Year:
2002

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Abstract

Fuzzy Stochastic Automata (FSA) are suitable for the modelling of the reactive (memoryless) learning and for the control of hybrid systems. The concept of FSA is to switch between a fuzzy increase and a fuzzy decrease of the control action according to the sign of the product e e, where e = x - xd is the error of the system's output and is its first derivative. The learning in FSA has stochastic features. The applications of FSA concern mainly autonomous systems and intelligent robots.