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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2507.19542 |
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| _version_ | 1866918104624267264 |
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| author | Shahbandari, Lida Mansouri, Mohammad |
| author_facet | Shahbandari, Lida Mansouri, Mohammad |
| contents | This study proposes optimized Type-I and Type-II fuzzy controllers for automotive suspension systems to enhance ride comfort and stability under road disturbances (step/sine inputs), addressing the lack of systematic performance comparisons in existing literature. We integrate Biogeography-Based Optimization (BBO), Particle Swarm Optimization (PSO), and Genetic Algorithms (GA) to tune controller parameters for a quarter car model, with emphasis on BBO's underexplored efficacy. MATLAB Simulink simulations demonstrate that BBO-optimized Type-II fuzzy control reduces body displacement by 22% and acceleration by 18% versus baseline methods under step disturbances, while maintaining computational efficiency. The framework provides practical, high-performance solutions for modern vehicles, particularly electric and autonomous platforms where vibration attenuation and energy efficiency are critical. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_19542 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Biogeography-Based Optimization of Fuzzy Controllers for Improved Quarter Car Suspension Performance Shahbandari, Lida Mansouri, Mohammad Systems and Control This study proposes optimized Type-I and Type-II fuzzy controllers for automotive suspension systems to enhance ride comfort and stability under road disturbances (step/sine inputs), addressing the lack of systematic performance comparisons in existing literature. We integrate Biogeography-Based Optimization (BBO), Particle Swarm Optimization (PSO), and Genetic Algorithms (GA) to tune controller parameters for a quarter car model, with emphasis on BBO's underexplored efficacy. MATLAB Simulink simulations demonstrate that BBO-optimized Type-II fuzzy control reduces body displacement by 22% and acceleration by 18% versus baseline methods under step disturbances, while maintaining computational efficiency. The framework provides practical, high-performance solutions for modern vehicles, particularly electric and autonomous platforms where vibration attenuation and energy efficiency are critical. |
| title | Biogeography-Based Optimization of Fuzzy Controllers for Improved Quarter Car Suspension Performance |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2507.19542 |