Liquid slosh suppression by implementing data-driven fractional order PID controller based on marine predators algorithm

Mohd Zaidi, Mohd Tumari and Mohd Ashraf, Ahmad and Mohd Riduwan, Ghazali and Nik Mohd Zaitul Akmal, Mustapha and Shahrizal, Saat (2023) Liquid slosh suppression by implementing data-driven fractional order PID controller based on marine predators algorithm. In: 2023 IEEE International Conference on Automatic Control and Intelligent Systems, I2CACIS 2023 - Proceedings , 17 June 2023 , Shah Alam, Malaysia. pp. 6-11.. ISBN 979-835032130-2 (Published)

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Abstract

Traditionally, the control system development of liquid slosh problems usually employed a model-based approach which is difficult to utilize practically since the fluid motion in the container is very chaotic and hard to model perfectly. Thus, this research paper proposed the development of a data-driven fractional-order PID controller based on marine predators algorithm (MPA) for liquid slosh suppression system. The MPA is used as a data-driven tuning tool in finding the optimal FOPID controller parameters based on fitness function which consists of total norm of tracking error, total norm of slosh angle as well as total norm of control input. The motor-driven liquid container performing a horizontal movement is used as a mathematical modeling to justify the suggested data-driven control approach. The effectiveness of the FOPID controller tuning method based on MPA was assessed by evaluating the performance criteria in terms of convergence curve of the average fitness function, statistical results, and Wilcoxon’s rank test. We have shown that the proposed data-driven tuning tool has a good ability in producing better results for the majority of the performance criteria as compared to other recent metaheuristic optimization algorithms.

Item Type:	Conference or Workshop Item (Paper)
Additional Information:	Indexed by Scopus
Uncontrolled Keywords:	Marine predators algorithm; Liquid slosh control; Metaheuristic optimization; Fractional order PID; Data-driven control
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division:	Faculty of Electrical and Electronic Engineering Technology Institute of Postgraduate Studies
Depositing User:	Mrs Norsaini Abdul Samat
Date Deposited:	13 Dec 2024 00:47
Last Modified:	13 Dec 2024 00:47
URI:	http://umpir.ump.edu.my/id/eprint/38207
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