A TS-type fuzzy automaton for software agents

Abstract

Tracking the status of an event-driven, large control system is a difficult problem. Those systems often encounter unexpected events in an uncertain environment. Using a fuzzy automaton offers an effective approximation method to model continuous and discrete signals in a single theoretical framework. A Max-Min automaton can successfully model a cluster of relevant states when a decision is to be made on the next state of a goal path at the supervisory level. However, to provide analytical proof for stability and other key properties of a fuzzy controller a Takagi-Sugeno model is preferred. In this paper a TS-type fuzzy automaton is proposed. The software architecture of an autonomous agent- based industrial control system is also outlined in which agents can utilize TS-type fuzzy automata.