Fuzzy Markov Modeling in Automatic Control of Complex Dynamic Systems

نویسنده

  • V. Arkov
چکیده

A novel modeling technique for automatic control purposes is discussed. A fuzzy Markov system is proposed to describe both determined and random behavior of complex dynamic plants. The main advantage is its high computational speed. Another benefit of this method is its flexibility and applicability to both linear and nonlinear systems. A controlled Markov chain represents a fuzzy system with a rectangular membership function. Its output is the probability distribution, not a variable value. This approach represents an attempt to overcome the primary difference between non-randomness of fuzzy sets and Markov chain theory, which deals with random phenomena.

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تاریخ انتشار 1999