An improved marine predators algorithm tuned data-driven multiple-node hormone regulation neuroendocrine-PID controller for multi-input–multi-output gantry crane system
Conventionally, researchers have favored the model-based control scheme for controlling gantry crane systems. However, this method necessitates a substantial investment of time and resources in order to develop an accurate mathematical model of the complex crane system. Recognizing this challenge, t...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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SAGE Publications Ltd
2023
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| Online Access: | http://umpir.ump.edu.my/id/eprint/38215/ http://umpir.ump.edu.my/id/eprint/38215/1/An%20improved%20marine%20predators%20algorithm%20tuned%20data-driven_FULL.pdf |
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| author | Mohd Zaidi, Mohd Tumari Mohd Ashraf, Ahmad Mohd Helmi, Suid Mohd Riduwan, Ghazali M Osman, Tokhi |
| author_facet | Mohd Zaidi, Mohd Tumari Mohd Ashraf, Ahmad Mohd Helmi, Suid Mohd Riduwan, Ghazali M Osman, Tokhi |
| author_sort | Mohd Zaidi, Mohd Tumari |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | Conventionally, researchers have favored the model-based control scheme for controlling gantry crane systems. However, this method necessitates a substantial investment of time and resources in order to develop an accurate mathematical model of the complex crane system. Recognizing this challenge, the current paper introduces a novel data-driven control scheme that relies exclusively on input and output data. Undertaking a couple of modifications to the conventional marine predators algorithm (MPA), random average marine predators algorithm (RAMPA) with tunable adaptive coefficient to control the step size (CF) has been proposed in this paper as an enhanced alternative towards fine-tuning data-driven multiple-node hormone regulation neuroendocrine-PID (MnHR-NEPID) controller parameters for the multi-input–multi-output (MIMO) gantry crane system. First modification involved a random average location calculation within the algorithm’s updating mechanism to solve the local optima issue. The second modification then introduced tunable CF that enhanced search capacity by enabling users’ resilience towards attaining an offsetting level of exploration and exploitation phases. Effectiveness of the proposed method is evaluated based on the convergence curve and statistical analysis of the fitness function, the total norms of error and input, Wilcoxon’s rank test, time response analysis, and robustness analysis under the influence of external disturbance. Comparative findings alongside other existing metaheuristic-based algorithms confirmed excellence of the proposed method through its superior performance against the conventional MPA, particle swarm optimization (PSO), grey wolf optimizer (GWO), moth-flame optimization (MFO), multi-verse optimizer (MVO), sine-cosine algorithm (SCA), salp-swarm algorithm (SSA), slime mould algorithm (SMA), flow direction algorithm (FDA), and the formally published adaptive safe experimentation dynamics (ASED)-based methods. |
| first_indexed | 2025-11-15T03:29:08Z |
| format | Article |
| id | ump-38215 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T03:29:08Z |
| publishDate | 2023 |
| publisher | SAGE Publications Ltd |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-382152023-08-03T01:58:53Z http://umpir.ump.edu.my/id/eprint/38215/ An improved marine predators algorithm tuned data-driven multiple-node hormone regulation neuroendocrine-PID controller for multi-input–multi-output gantry crane system Mohd Zaidi, Mohd Tumari Mohd Ashraf, Ahmad Mohd Helmi, Suid Mohd Riduwan, Ghazali M Osman, Tokhi TK Electrical engineering. Electronics Nuclear engineering Conventionally, researchers have favored the model-based control scheme for controlling gantry crane systems. However, this method necessitates a substantial investment of time and resources in order to develop an accurate mathematical model of the complex crane system. Recognizing this challenge, the current paper introduces a novel data-driven control scheme that relies exclusively on input and output data. Undertaking a couple of modifications to the conventional marine predators algorithm (MPA), random average marine predators algorithm (RAMPA) with tunable adaptive coefficient to control the step size (CF) has been proposed in this paper as an enhanced alternative towards fine-tuning data-driven multiple-node hormone regulation neuroendocrine-PID (MnHR-NEPID) controller parameters for the multi-input–multi-output (MIMO) gantry crane system. First modification involved a random average location calculation within the algorithm’s updating mechanism to solve the local optima issue. The second modification then introduced tunable CF that enhanced search capacity by enabling users’ resilience towards attaining an offsetting level of exploration and exploitation phases. Effectiveness of the proposed method is evaluated based on the convergence curve and statistical analysis of the fitness function, the total norms of error and input, Wilcoxon’s rank test, time response analysis, and robustness analysis under the influence of external disturbance. Comparative findings alongside other existing metaheuristic-based algorithms confirmed excellence of the proposed method through its superior performance against the conventional MPA, particle swarm optimization (PSO), grey wolf optimizer (GWO), moth-flame optimization (MFO), multi-verse optimizer (MVO), sine-cosine algorithm (SCA), salp-swarm algorithm (SSA), slime mould algorithm (SMA), flow direction algorithm (FDA), and the formally published adaptive safe experimentation dynamics (ASED)-based methods. SAGE Publications Ltd 2023-06 Article PeerReviewed pdf en cc_by_4 http://umpir.ump.edu.my/id/eprint/38215/1/An%20improved%20marine%20predators%20algorithm%20tuned%20data-driven_FULL.pdf Mohd Zaidi, Mohd Tumari and Mohd Ashraf, Ahmad and Mohd Helmi, Suid and Mohd Riduwan, Ghazali and M Osman, Tokhi (2023) An improved marine predators algorithm tuned data-driven multiple-node hormone regulation neuroendocrine-PID controller for multi-input–multi-output gantry crane system. Journal of Low Frequency Noise, Vibration and Active Control. pp. 1-33. ISSN 1461-3484 (Print), 2048-4046 (Online). (In Press / Online First) (In Press / Online First) https://doi.org/10.1177/146134842311839 https://doi.org/10.1177/146134842311839 |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Mohd Zaidi, Mohd Tumari Mohd Ashraf, Ahmad Mohd Helmi, Suid Mohd Riduwan, Ghazali M Osman, Tokhi An improved marine predators algorithm tuned data-driven multiple-node hormone regulation neuroendocrine-PID controller for multi-input–multi-output gantry crane system |
| title | An improved marine predators algorithm tuned data-driven multiple-node hormone regulation neuroendocrine-PID controller for multi-input–multi-output gantry crane system |
| title_full | An improved marine predators algorithm tuned data-driven multiple-node hormone regulation neuroendocrine-PID controller for multi-input–multi-output gantry crane system |
| title_fullStr | An improved marine predators algorithm tuned data-driven multiple-node hormone regulation neuroendocrine-PID controller for multi-input–multi-output gantry crane system |
| title_full_unstemmed | An improved marine predators algorithm tuned data-driven multiple-node hormone regulation neuroendocrine-PID controller for multi-input–multi-output gantry crane system |
| title_short | An improved marine predators algorithm tuned data-driven multiple-node hormone regulation neuroendocrine-PID controller for multi-input–multi-output gantry crane system |
| title_sort | improved marine predators algorithm tuned data-driven multiple-node hormone regulation neuroendocrine-pid controller for multi-input–multi-output gantry crane system |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | http://umpir.ump.edu.my/id/eprint/38215/ http://umpir.ump.edu.my/id/eprint/38215/ http://umpir.ump.edu.my/id/eprint/38215/ http://umpir.ump.edu.my/id/eprint/38215/1/An%20improved%20marine%20predators%20algorithm%20tuned%20data-driven_FULL.pdf |