Abstract
Minimum entropy control technique, an approach for controlling chaos without using the dynamical model of the system, can be improved by being combined with a nature-based optimization technique. In this paper, an ACO-based optimization algorithm is employed to minimize the entropy function of the chaotic system. The feedback gain of a delayed feedback controller is adjusted in the ACO algorithm. The effectiveness of the idea is investigated on suppressing chaos in the tapping-mode atomic force microscope equations. Results show a good performance. The PSO-based version of the minimum entropy control technique is also used to control the chaotic behavior of the AFM, and corresponding results are compared showing almost a same functionality for the two optimization algorithms of PSO and ACO as the minimizing engines of the minimum entropy strategy.
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