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Metaheuristic algorithms for PID controller parameters tuning: review, approaches and open problems

期刊

HELIYON
卷 8, 期 5, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.heliyon.2022.e09399

关键词

PID controller; Tuning; Metaheuristic algorithm; Softcomputing; Machine learning; PID controller; Tuning; Metaheuristic algorithm; Softcomputing; Machine learning

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This paper provides a comprehensive review of modern and classical strategies for tuning PID controller parameters using metaheuristic algorithms. It also presents some open problems for future research.
The simplicity, transparency, reliability, high efficiency and robust nature of PID controllers are some of the reasons for their high popularity and acceptance for control in process industries around the world today. Tuning of PID control parameters has been a field of active research and still is. The primary objectives of PID control parameters are to achieve minimal overshoot in steady state response and lesser settling time. With exception of two popular conventional tuning strategies (Ziegler Nichols closed loop oscillation and Cohen-Coon's process reaction curve) several other methods have been employed for tuning. This work accords a thorough review of state-of-the-art and classical strategies for PID controller parameters tuning using metaheuristic algorithms. Methods appraised are categorized into classical and metaheuristic optimization methods for PID parameters tuning purposes. Details of some metaheuristic algorithms, methods of application, equations and implementation flowcharts/algorithms are presented. Some open problems for future research are also presented. The major goal of this work is to proffer a comprehensive reference source for researchers and scholars working on PID controllers.

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