IEEE Access (Jan 2022)

Improved MM-MADRL Algorithm for Automatic Tuning of Multiparameter Control Systems

  • Hongming Zhang,
  • Wudhichai Assawinchaichote,
  • Yan Shi

DOI
https://doi.org/10.1109/ACCESS.2022.3184002
Journal volume & issue
Vol. 10
pp. 64729 – 64740

Abstract

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Control systems are widely used in our lives, and good control can be achieved by obtaining the optimal tuning parameters of the control system. The number of parameters that need to be adjusted for different control systems varies. With an increase in tuning parameters, the difficulty of tuning grows. Therefore, this paper proposes an improved monkey multiagent DRL (IMM-MADRL) algorithm and selects 3 test functions to test the setting environment of 2–7 parameters. Thus, these parameters are adjusted. The IMM-MADRL algorithm is based on the modified monkey-multiagent DRL (MM-MADRL) algorithm, and its initialization method, position update method and somersault operation are further improved so that it can perform good parameter tuning for a control system with many parameters. The simulation part of this paper proves the advantage of the IMM-MADRL algorithm in a multiparameter control system.

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