Accelerated black hole optimization algorithm with enhanced FOPID controller for omni-wheel drive mobile robot system
Controlling Omni-Wheel Drive Mobile Robot Systems (OWDMRS) presents unique challenges due to their ability to move in multiple directions such as rotation, sideways, and forward/backward motion while minimizing energy consumption and voltage fluctuations. This study introduces a novel framework that...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Springer Science and Business Media Deutschland GmbH
2025
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| Online Access: | http://psasir.upm.edu.my/id/eprint/120774/ http://psasir.upm.edu.my/id/eprint/120774/1/120774.pdf |
| _version_ | 1848868223698599936 |
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| author | Basil, Noorulden Marhoon, Hamzah M. Sahib, Dheyaaldeen Faez Mohammed, Abdullah Fadhil Ridha, Hussein Mohammed Ma’arif, Alfian |
| author_facet | Basil, Noorulden Marhoon, Hamzah M. Sahib, Dheyaaldeen Faez Mohammed, Abdullah Fadhil Ridha, Hussein Mohammed Ma’arif, Alfian |
| author_sort | Basil, Noorulden |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Controlling Omni-Wheel Drive Mobile Robot Systems (OWDMRS) presents unique challenges due to their ability to move in multiple directions such as rotation, sideways, and forward/backward motion while minimizing energy consumption and voltage fluctuations. This study introduces a novel framework that enhances motion control and trajectory tracking by integrating an advanced fractional-order proportional–integral–derivative (FOPID) controller with an adaptive neuro-fuzzy inference system (ANFIS). To optimize controller performance, six different optimization algorithms are compared are Accelerated Convergence Black Hole Optimization (ACBHO), Black Hole Optimization (BHO), Aquila Optimizer (AO), Hybrid Firefly Particle Swarm Optimization (HFPSO), Enhanced JAYA (EJAYA), and Sunflower Optimizer (SFO). Among these, the proposed ACBHO algorithm significantly improved trajectory tracking accuracy and control efficiency. The framework effectively manages voltage regulation and enhances motion precision by fine-tuning FOPID and ANFIS parameters. These results demonstrate the potential of ACBHO-based optimization as a robust solution for improving control system performance in advanced mobile robotics applications. |
| first_indexed | 2025-11-15T14:48:59Z |
| format | Article |
| id | upm-120774 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T14:48:59Z |
| publishDate | 2025 |
| publisher | Springer Science and Business Media Deutschland GmbH |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-1207742025-10-10T01:35:12Z http://psasir.upm.edu.my/id/eprint/120774/ Accelerated black hole optimization algorithm with enhanced FOPID controller for omni-wheel drive mobile robot system Basil, Noorulden Marhoon, Hamzah M. Sahib, Dheyaaldeen Faez Mohammed, Abdullah Fadhil Ridha, Hussein Mohammed Ma’arif, Alfian Controlling Omni-Wheel Drive Mobile Robot Systems (OWDMRS) presents unique challenges due to their ability to move in multiple directions such as rotation, sideways, and forward/backward motion while minimizing energy consumption and voltage fluctuations. This study introduces a novel framework that enhances motion control and trajectory tracking by integrating an advanced fractional-order proportional–integral–derivative (FOPID) controller with an adaptive neuro-fuzzy inference system (ANFIS). To optimize controller performance, six different optimization algorithms are compared are Accelerated Convergence Black Hole Optimization (ACBHO), Black Hole Optimization (BHO), Aquila Optimizer (AO), Hybrid Firefly Particle Swarm Optimization (HFPSO), Enhanced JAYA (EJAYA), and Sunflower Optimizer (SFO). Among these, the proposed ACBHO algorithm significantly improved trajectory tracking accuracy and control efficiency. The framework effectively manages voltage regulation and enhances motion precision by fine-tuning FOPID and ANFIS parameters. These results demonstrate the potential of ACBHO-based optimization as a robust solution for improving control system performance in advanced mobile robotics applications. Springer Science and Business Media Deutschland GmbH 2025 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/120774/1/120774.pdf Basil, Noorulden and Marhoon, Hamzah M. and Sahib, Dheyaaldeen Faez and Mohammed, Abdullah Fadhil and Ridha, Hussein Mohammed and Ma’arif, Alfian (2025) Accelerated black hole optimization algorithm with enhanced FOPID controller for omni-wheel drive mobile robot system. Neural Computing and Applications, 37 (21). pp. 16983-17014. ISSN 0941-0643; eISSN: 1433-3058 https://link.springer.com/article/10.1007/s00521-025-11310-6?error=cookies_not_supported&code=f5c8f06f-2d0a-4802-a869-319497d1ad54 10.1007/s00521-025-11310-6 |
| spellingShingle | Basil, Noorulden Marhoon, Hamzah M. Sahib, Dheyaaldeen Faez Mohammed, Abdullah Fadhil Ridha, Hussein Mohammed Ma’arif, Alfian Accelerated black hole optimization algorithm with enhanced FOPID controller for omni-wheel drive mobile robot system |
| title | Accelerated black hole optimization algorithm with enhanced FOPID controller for omni-wheel drive mobile robot system |
| title_full | Accelerated black hole optimization algorithm with enhanced FOPID controller for omni-wheel drive mobile robot system |
| title_fullStr | Accelerated black hole optimization algorithm with enhanced FOPID controller for omni-wheel drive mobile robot system |
| title_full_unstemmed | Accelerated black hole optimization algorithm with enhanced FOPID controller for omni-wheel drive mobile robot system |
| title_short | Accelerated black hole optimization algorithm with enhanced FOPID controller for omni-wheel drive mobile robot system |
| title_sort | accelerated black hole optimization algorithm with enhanced fopid controller for omni-wheel drive mobile robot system |
| url | http://psasir.upm.edu.my/id/eprint/120774/ http://psasir.upm.edu.my/id/eprint/120774/ http://psasir.upm.edu.my/id/eprint/120774/ http://psasir.upm.edu.my/id/eprint/120774/1/120774.pdf |