Symbiotic organisms search algorithm for optimal evolutionary controller tuning of fractional fuzzy controllers

Abstract With the development of technology and the practical needs of complex engineering applications, fuzzy controllers have been widely applied. In contrast to a traditional integer-order fuzzy controller, a fractional fuzzy controller can extend the integral and differential order of a fuzzy controller to any real number, which describes the controlled object more accurately and enhances its control performance. However, a fractional fuzzy controller has a larger number of control parameters, which makes it difficult to calibrate. Because the parameter controller tuning values of the fuzzy controller clearly influence its control performance, this paper proposes to optimize the parameter controller tuning process using the symbiotic organisms search algorithm. A large number of simulation tests were carried out to compare the symbiotic organisms search-based parameter controller tuning method with parameter controller tuning based on five other representative swarm intelligence algorithms. The experimental results show that the symbiotic organisms search algorithm better optimizes the parameters of the fractional fuzzy controller.

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