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Particle Swarm Optimization of Real-Time PID Controllers

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Handbook of Real-Time Computing

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Abstract

Particle swarm optimization (PSO) is a stochastic population-based algorithm based on the collaborative swarm behaviors of insects, birds, fish, and animals. The algorithms use swarm emulation to seek for solutions to optimization problems and are often used for the optimization of continuous nonlinear systems. This approach has recently succeeded in addressing many significant real-world optimization problems. In particular, this work integrates studies of PSOs and proportional–integral–derivative (PID) controllers, which are widely used for industrial control, in order to optimize PID controllers using PSO in a wide variety of multidisciplinary fields. This chapter introduces the PSO approach and algorithm and the theory of PID control, the use of PSO in optimizing the parameters of various controllers, and illustrates the findings by exploring several real-time control applications.

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Author information

Authors and Affiliations

  1. School of Electrical and Information Engineering, The University of Sydney, Sydney, NSW, Australia

    David C. Levy

  2. School of Software Engineering, Huazhong University of Science and Technology, Wuhan, China

    Yongzhong Lu

  3. College of Public Administration, Huazhong University of Science and Technology, Wuhan, China

    Danping Yan & Min Zhou

  4. Data61, Commonwealth Scientific and Industrial Research Organization, Marsfield, NSW, Australia

    Shiping Chen

Authors
  1. David C. Levy
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  2. Yongzhong Lu
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  3. Danping Yan
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  4. Min Zhou
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  5. Shiping Chen
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Corresponding author

Correspondence to David C. Levy .

Editor information

Editors and Affiliations

  1. School of Computer Science, Queensland University of Technology, Brisbane, QLD, Australia

    Yu-Chu Tian

  2. School of Electrical and Information Engineering, The University of Sydney, Sydney, NSW, Australia

    David Charles Levy

Section Editor information

  1. Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai, China

    Yang Tang

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Levy, D.C., Lu, Y., Yan, D., Zhou, M., Chen, S. (2022). Particle Swarm Optimization of Real-Time PID Controllers. In: Tian, YC., Levy, D.C. (eds) Handbook of Real-Time Computing. Springer, Singapore. https://doi.org/10.1007/978-981-287-251-7_49

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