An improved convergence particle swarm optimization algorithm with random sampling of control parameters

DOI10.1155/2019/7478498zbMath1432.93315OpenAlexW2947179124WikidataQ127780396 ScholiaQ127780396MaRDI QIDQ2303400

Xiaodong Song, Tianfei Chen, Lijun Sun

Publication date: 3 March 2020

Published in: Journal of Control Science and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2019/7478498

zbMATH Keywords

particle swarm optimization algorithmrandom sampling of control parameters

Mathematics Subject Classification ID

Approximation methods and heuristics in mathematical programming (90C59) Stochastic systems in control theory (general) (93E03)

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Cites Work

• Estimation of stator resistance and rotor flux linkage in SPMSM using CLPSO with opposition-based-learning strategy
• The particle swarm optimization algorithm: Convergence analysis and parameter selection
• Consensus control of second-order multiagent systems with particle swarm optimization algorithm
• A study of particle swarm optimization particle trajectories
• Analysis of Standard Particle Swarm Optimization Algorithm Based on Markov Chain
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