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PID control for chaotic synchronization using particle swarm optimization

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  • Chang, Wei-Der

Abstract

In this paper, we attempt to use the proportional-integral-derivative (PID) controller to achieve the chaos synchronization for delayed discrete chaotic systems. Three PID control gains can be optimally determined by means of using a novel optimization algorithm, called the particle swarm optimization (PSO). The algorithm is motivated from the organism behavior of fish schooling and bird flocking, and involves the social psychology principles in socio-cognition human agents and evolutionary computations. It has a good numerical convergence for solving optimization problem. To show the validity of the PSO-based PID control for chaos synchronization, several cases with different initial populations are considered and some simulation results are shown.

Suggested Citation

  • Chang, Wei-Der, 2009. "PID control for chaotic synchronization using particle swarm optimization," Chaos, Solitons & Fractals, Elsevier, vol. 39(2), pages 910-917.
    • Handle: RePEc:eee:chsofr:v:39:y:2009:i:2:p:910-917
    DOI: 10.1016/j.chaos.2007.01.064
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    References listed on IDEAS

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    1. Li, Guo-Hui, 2006. "Generalized projective synchronization of two chaotic systems by using active control," Chaos, Solitons & Fractals, Elsevier, vol. 30(1), pages 77-82.
    2. Park, Ju H., 2005. "Chaos synchronization of a chaotic system via nonlinear control," Chaos, Solitons & Fractals, Elsevier, vol. 25(3), pages 579-584.
    3. Yassen, M.T., 2005. "Controlling chaos and synchronization for new chaotic system using linear feedback control," Chaos, Solitons & Fractals, Elsevier, vol. 26(3), pages 913-920.
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    Cited by:

    1. Coelho, Leandro dos Santos & Mariani, Viviana Cocco, 2009. "Chaotic artificial immune approach applied to economic dispatch of electric energy using thermal units," Chaos, Solitons & Fractals, Elsevier, vol. 40(5), pages 2376-2383.
    2. Coelho, Leandro dos Santos & Bernert, Diego Luis de Andrade, 2009. "PID control design for chaotic synchronization using a tribes optimization approach," Chaos, Solitons & Fractals, Elsevier, vol. 42(1), pages 634-640.
    3. Hallaji, Majid & Dideban, Abbas & Khanesar, Mojtaba Ahmadieh & kamyad, Ali vahidyan, 2018. "Optimal synchronization of non-smooth fractional order chaotic systems with uncertainty based on extension of a numerical approach in fractional optimal control problems," Chaos, Solitons & Fractals, Elsevier, vol. 115(C), pages 325-340.
    4. Alsaade, Fawaz W. & Yao, Qijia & Bekiros, Stelios & Al-zahrani, Mohammed S. & Alzahrani, Ali S. & Jahanshahi, Hadi, 2022. "Chaotic attitude synchronization and anti-synchronization of master-slave satellites using a robust fixed-time adaptive controller," Chaos, Solitons & Fractals, Elsevier, vol. 165(P2).
    5. Mohamed A. Tawhid & Ahmed F. Ali, 2016. "Simplex particle swarm optimization with arithmetical crossover for solving global optimization problems," OPSEARCH, Springer;Operational Research Society of India, vol. 53(4), pages 705-740, December.
    6. Sarita Devi & Deepika Garg, 2020. "Hybrid genetic and particle swarm algorithm: redundancy allocation problem," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(2), pages 313-319, April.

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