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

Autor: Hongming Zhang, Wudhichai Assawinchaichote, Yan Shi
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: IEEE Access, Vol 10, Pp 64729-64740 (2022)
Druh dokumentu: article
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2022.3184002
Popis: 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.
Databáze: Directory of Open Access Journals