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PID parameters tuning based on improved PSO algorithm

Yunping Chen

Open publisher page 3 citations

Abstract

Particle swarm optimization(PSO) is a new evolutionary computation method with simple algorithm and excellent optimization performance of Matlab recently.In this paper,improved PSO is used to optimize PID parameters of the example in the paper combining with powerful matrix computing and system simulation functions.Simulation shows that its optimization result and convergence performance are better than that of genetic algorithm.

About this research paper

What this paper is about

Particle swarm optimization(PSO) is a new evolutionary computation method with simple algorithm and excellent optimization performance of Matlab recently.In this paper,improved PSO is used to optimize PID parameters of the example in the paper combining with powerful matrix computing and system simulation functions.Simulation shows that its optimization result and convergence performance are better than that of genetic algorithm.

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OpenAlex reports 3 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Particle swarm optimization(PSO) is a new evolutionary computation method with simple algorithm and excellent optimization performance of Matlab recently.In this paper,improved PSO is used to optimize PID parameters of the example in the paper combining with powerful matrix computing and system simulation functions.Simulation shows that its optimization result and convergence performance are better than that of genetic algorithm.

Key concepts: Particle swarm optimization, PID controller, MATLAB, Computer science, Convergence (economics), Genetic algorithm, Computation, Mathematical optimization

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