Robustness multi-objective optimization for parallel robot based on subregional meta-heuristic iteration
Purpose – This work aims to provide a rapid robust optimization design solution for parallel robots or mechanisms, thereby circumventing inefficiencies and wastage caused by empirical design, as well as numerous physical verifications, which can be employed for creating high-quality prototypes of pa...
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| Format: | Article |
| Language: | English |
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Emerald Publishing
2024-12-01
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| Series: | Journal of Intelligent Manufacturing and Special Equipment |
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| Online Access: | https://www.emerald.com/insight/content/doi/10.1108/JIMSE-06-2024-0016/full/pdf |
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| _version_ | 1846139704052809728 |
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| author | Mingzhe Tao Jinghua Xu Shuyou Zhang Jianrong Tan |
| author_facet | Mingzhe Tao Jinghua Xu Shuyou Zhang Jianrong Tan |
| author_sort | Mingzhe Tao |
| collection | DOAJ |
| description | Purpose – This work aims to provide a rapid robust optimization design solution for parallel robots or mechanisms, thereby circumventing inefficiencies and wastage caused by empirical design, as well as numerous physical verifications, which can be employed for creating high-quality prototypes of parallel robots in a variety of applications. Design/methodology/approach – A novel subregional meta-heuristic iteration (SMI) method is proposed for the optimization of parallel robots. Multiple subregional optimization objectives are established and optimization is achieved through the utilisation of an enhanced meta-heuristic optimization algorithm, which roughly employs chaotic mapping in the initialization strategy to augment the diversity of the initial solution. The non-dominated sorting method is utilised for updating strategies, thereby achieving multi-objective optimization. Findings – The actuator error under the same trajectory is visibly reduced after SMI, with a maximum reduction of 6.81% and an average reduction of 1.46%. Meanwhile, the response speed, maximum bearing capacity and stiffness of the mechanism are enhanced by 63.83, 43.98 and 97.51%, respectively. The optimized mechanism is more robust and the optimization process is efficient. Originality/value – The proposed robustness multi-objective optimization via SMI is more effective in improving the performance and precision of the parallel mechanisms in various applications. Furthermore, it provides a solution for the rapid and high-quality optimization design of parallel robots. |
| format | Article |
| id | doaj-art-73ffcb3f6ae04f7daaf6eeca960bef6f |
| institution | Kabale University |
| issn | 2633-6596 2633-660X |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Emerald Publishing |
| record_format | Article |
| series | Journal of Intelligent Manufacturing and Special Equipment |
| spelling | doaj-art-73ffcb3f6ae04f7daaf6eeca960bef6f2024-12-06T06:55:35ZengEmerald PublishingJournal of Intelligent Manufacturing and Special Equipment2633-65962633-660X2024-12-015329430010.1108/JIMSE-06-2024-0016Robustness multi-objective optimization for parallel robot based on subregional meta-heuristic iterationMingzhe Tao0Jinghua Xu1Shuyou Zhang2Jianrong Tan3State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou, ChinaState Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou, ChinaState Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou, ChinaState Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou, ChinaPurpose – This work aims to provide a rapid robust optimization design solution for parallel robots or mechanisms, thereby circumventing inefficiencies and wastage caused by empirical design, as well as numerous physical verifications, which can be employed for creating high-quality prototypes of parallel robots in a variety of applications. Design/methodology/approach – A novel subregional meta-heuristic iteration (SMI) method is proposed for the optimization of parallel robots. Multiple subregional optimization objectives are established and optimization is achieved through the utilisation of an enhanced meta-heuristic optimization algorithm, which roughly employs chaotic mapping in the initialization strategy to augment the diversity of the initial solution. The non-dominated sorting method is utilised for updating strategies, thereby achieving multi-objective optimization. Findings – The actuator error under the same trajectory is visibly reduced after SMI, with a maximum reduction of 6.81% and an average reduction of 1.46%. Meanwhile, the response speed, maximum bearing capacity and stiffness of the mechanism are enhanced by 63.83, 43.98 and 97.51%, respectively. The optimized mechanism is more robust and the optimization process is efficient. Originality/value – The proposed robustness multi-objective optimization via SMI is more effective in improving the performance and precision of the parallel mechanisms in various applications. Furthermore, it provides a solution for the rapid and high-quality optimization design of parallel robots.https://www.emerald.com/insight/content/doi/10.1108/JIMSE-06-2024-0016/full/pdfRobustness multi-objective optimizationLogistics parallel robotSubregional meta-heuristic iteration (SMI) |
| spellingShingle | Mingzhe Tao Jinghua Xu Shuyou Zhang Jianrong Tan Robustness multi-objective optimization for parallel robot based on subregional meta-heuristic iteration Journal of Intelligent Manufacturing and Special Equipment Robustness multi-objective optimization Logistics parallel robot Subregional meta-heuristic iteration (SMI) |
| title | Robustness multi-objective optimization for parallel robot based on subregional meta-heuristic iteration |
| title_full | Robustness multi-objective optimization for parallel robot based on subregional meta-heuristic iteration |
| title_fullStr | Robustness multi-objective optimization for parallel robot based on subregional meta-heuristic iteration |
| title_full_unstemmed | Robustness multi-objective optimization for parallel robot based on subregional meta-heuristic iteration |
| title_short | Robustness multi-objective optimization for parallel robot based on subregional meta-heuristic iteration |
| title_sort | robustness multi objective optimization for parallel robot based on subregional meta heuristic iteration |
| topic | Robustness multi-objective optimization Logistics parallel robot Subregional meta-heuristic iteration (SMI) |
| url | https://www.emerald.com/insight/content/doi/10.1108/JIMSE-06-2024-0016/full/pdf |
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