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Fitness peak clustering based dynamic multi-swarm particle swarm optimization with enhanced learning strategy

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Summary: This paper introduces five new contributions to the state-of-the-art in fuzzy controller tuning. It proposes a fresh metaheuristic algorithm, the Slime Mould Algorithm (SMA), for optimal tuning of cost-effective fuzzy controllers. The study also presents a real-world application of SMA focusing on the optimal tuning of TSK PI-FCs for nonlinear servo systems, highlighting the superiority of SMA over other metaheuristic algorithms in solving the same optimization problem.

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