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This paper investigates horizontal crossover (HC) and stability-based adaptive inertia weight (SAIW) strategies for comprehensive learning particle swarm optimization. HC applies arithmetic crossover on all the dimensions of two different personal best positions. SAIW adaptively adjusts the inertia weight and acceleration coefficient for each particle on each dimension. Experimental results on various...
The main objective of this paper is to revisit one of the key steps of immersion and invariance stabilizing controller design. Namely, the one that ensures attractivity of the manifold whose internal dynamics contains a copy of the desired system behavior. Towards this end we invoke contraction theory principles and propose two alternative procedures to carry out this step: (i) to replace attractivity...
This paper presents a novel swarm approximate dynamic programming method (swarm-ADP) for parameter optimization of PSO systems, from the perspective of optimal control. Based on the stability results of a simplified PSO and the swarm-ADP algorithm, parameter dynamic optimization and computation is studied in detail for a deterministic PSO system and a stochastic PSO system, respectively. Furthermore,...
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