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ACS algorithm-based adaptive fuzzy PID controller and its application to CIP-I intelligent leg

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Abstract

Based on the ant colony system (ACS) algorithm and fuzzy logic control, a new design method for optimal fuzzy PID controller was proposed. In this method, the ACS algorithm was used to optimize the input/output scaling factors of fuzzy PID controller to generate the optimal fuzzy control rules and optimal real-time control action on a given controlled object. The designed controller, called the Fuzzy-ACS PID controller, was used to control the CIP-I intelligent leg. The simulation experiments demonstrate that this controller has good control performance. Compared with other three optimal PID controllers designed respectively by using the differential evolution algorithm, the real-coded genetic algorithm, and the simulated annealing, it was verified that the Fuzzy-ACS PID controller has better control performance. Furthermore, the simulation results also verify that the proposed ACS algorithm has quick convergence speed, small solution variation, good dynamic convergence behavior, and high computation efficiency in searching for the optimal input/output scaling factors.

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Authors and Affiliations

  1. School of Information Science and Engineering, Central South University, Changsha, 410083, China

    Tan Guan-zheng PhD  (谭冠政) (Professor) & Dou Hong-quan  (窦红权)

Authors
  1. Tan Guan-zheng PhD  (谭冠政)
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  2. Dou Hong-quan  (窦红权)
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Corresponding author

Correspondence to Tan Guan-zheng PhD  (谭冠政).

Additional information

Foundation item: Project(50275150) supported by the National Natural Science Foundation of China; Project(20040533035) supported by the National Research Foundation for the Doctoral Program of Higher Education of China; Project(05JJ40128) supported by the Natural Science Foundation of Hunan Province, China

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Tan, Gz., Dou, Hq. ACS algorithm-based adaptive fuzzy PID controller and its application to CIP-I intelligent leg. J Cent. South Univ. Technol. 14, 528–536 (2007). https://doi.org/10.1007/s11771-007-0103-3

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  • DOI: https://doi.org/10.1007/s11771-007-0103-3

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