Abstract
The chaotic ant swarm (CAS) algorithm is inspired by the chaotic and self-organization behavior of ants. It belongs to the categories of chaos optimization methods and swarm intelligence approaches. This paper presents the CAS-designed fuzzy system can be used effectively to achieve the adaptive control of dynamical systems. The design of the fuzzy system is comprised of the extraction of “if-then” rules that is followed by the identification of their parameters. The involved parameters include those that determine the membership function of fuzzy sets and the certainty factors of fuzzy if-then rules. The position vector of each ant in the CAS algorithm corresponds to the parameter vector of the selected T-S fuzzy system. At each learning time step, the CAS algorithm is iterated to give the optimal parameters of fuzzy system based on the fitness theory. Then the corresponding CAS-designed T-S fuzzy system is built and applied to the adaptive control of the unknown nonlinear dynamical systems. Numerical simulations are provided to verify the effectiveness and feasibility of the developed CAS-designed T-S fuzzy system.
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