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- W2349663350 abstract "The performance of control system is determined by the control parameter of controller. Aimed at the puzzle of parameter selection for particle swarm optimization (PSO) control algorithm that the phenomenon of premature convergence made the basic PSO algorithms have been easy to get in local optimal solution, and resulted in impossible convergence to global extremum, as well as being not so high in search precision and slower in convergence speed, the paper proposed a sort of improved control algorithm based on particle swarm optimization. In the paper, it discussed the particle swarm optimization algorithms with genetic thought (GAPSO), researched on improved algorithm of PSO, and made the comparative study for proposed control algorithm by means of simulation experiment. The response curve of simulation result demonstrated that it would be better in comparison with conventional method in dynamic and steady performance, and verified the reasonability and feasibility of the improved control algorithm. The research result shows that the improved algorithm of PSO proposed by the paper is more effective for controller parameter tuning." @default.
- W2349663350 created "2016-06-24" @default.
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- W2349663350 date "2012-01-01" @default.
- W2349663350 modified "2023-09-26" @default.
- W2349663350 title "Improved Control Algorithm Based on Particle Swarm Optimization and Its Simulation Research" @default.
- W2349663350 hasPublicationYear "2012" @default.
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