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A new particle swarm optimization based auto-tuning of PID controller

Youbo Wang, Xin Peng, Benzheng Wei

Open publisher page 39 citations

Abstract

Particle swarm optimization based auto-tuning of Proportional-Integral-Derivative (PID) controller is discussed in this paper. Relay feedback experiment is applied to identify the approximate parameters of PID controller first, although the parameters identified is not very accurate. Next we utilize particle swarm optimization algorithm to refining parameters of PID controller. The basic particle swarm optimization based auto tuning PID algorithm often fall into local optimum. To improve the performance of controller, an improved PSO method is proposed in this paper by dividing the searching process into two steps. First the parameter kdof particles is limited in a small space then enlarged to a larger one. Our experiments confirm the method can improve the perform ance of PID controller dramatically.

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What this paper is about

Particle swarm optimization based auto-tuning of Proportional-Integral-Derivative (PID) controller is discussed in this paper. Relay feedback experiment is applied to identify the approximate parameters of PID controller first, although the parameters identified is not very accurate. Next we utilize particle swarm optimization algorithm to refining parameters of PID controller. The basic particle swarm optimization based auto tuning PID algorithm often fall into local optimum. To improve the performance of controller, an improved PSO method is proposed in this paper by dividing the searching process into two steps. First the parameter kdof particles is limited in a small space then enlarged to a larger one. Our experiments confirm the method can improve the perform ance of PID controller dramatically.

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OpenAlex reports 39 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Particle swarm optimization based auto-tuning of Proportional-Integral-Derivative (PID) controller is discussed in this paper. Relay feedback experiment is applied to identify the approximate parameters of PID controller first, although the parameters identified is not very accurate. Next we utilize particle swarm optimization algorithm to refining parameters of PID controller. The basic particle swarm optimization based auto tuning PID algorithm often fall into local optimum. To improve the performance of controller, an improved PSO method is proposed in this paper by dividing the searching process into two steps. First the parameter kdof particles is limited in a small space then enlarged to a larger one. Our experiments confirm the method can improve the perform ance of PID controller dramatically.

Key concepts: PID controller, Particle swarm optimization, Control theory (sociology), Controller (irrigation), Computer science, Control engineering, Algorithm, Engineering

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