Optimized Fuzzy Skyhook Control for Semi-Active Vehicle Suspension with New Inverse Model of Magnetorheological Fluid Damper
To improve the performance of vehicle suspension, this paper proposes a semi-active vehicle suspension with a magnetorheological fluid (MRF) damper. We designed an optimized fuzzy skyhook controller with grey wolf optimizer (GWO) algorithm base on a new neuro-inverse model of the MRF damper. Because...
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MDPI AG
2021-03-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/14/6/1674 |
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| author | Teng Ma Fengrong Bi Xu Wang Congfeng Tian Jiewei Lin Jie Wang Gejun Pang |
| author_facet | Teng Ma Fengrong Bi Xu Wang Congfeng Tian Jiewei Lin Jie Wang Gejun Pang |
| author_sort | Teng Ma |
| collection | DOAJ |
| description | To improve the performance of vehicle suspension, this paper proposes a semi-active vehicle suspension with a magnetorheological fluid (MRF) damper. We designed an optimized fuzzy skyhook controller with grey wolf optimizer (GWO) algorithm base on a new neuro-inverse model of the MRF damper. Because the inverse model of the MRF damper is difficult to establish directly, the Elman neural network was applied. The novelty of this study is the application of the new inverse model for semi-active vibration control and optimization of the semi-active suspension control method. The calculation results showed that the new inverse model can accurately calculate the required control current. The fuzzy skyhook control method optimized by the grey wolf optimizer (GWO) algorithm was established based on the inverse model to control the suspension vibration. The simulation results showed that the optimized fuzzy skyhook control method can simultaneously reduce the amplitude of vertical acceleration, suspension deflection, and tire dynamic load. |
| first_indexed | 2024-03-10T13:08:55Z |
| format | Article |
| id | doaj.art-b1490e4f05554f7592408bd3cb5592a1 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T13:08:55Z |
| publishDate | 2021-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-b1490e4f05554f7592408bd3cb5592a12023-11-21T10:55:04ZengMDPI AGEnergies1996-10732021-03-01146167410.3390/en14061674Optimized Fuzzy Skyhook Control for Semi-Active Vehicle Suspension with New Inverse Model of Magnetorheological Fluid DamperTeng Ma0Fengrong Bi1Xu Wang2Congfeng Tian3Jiewei Lin4Jie Wang5Gejun Pang6State Key Laboratory of Engines, Tianjin University, Tianjin 300072, ChinaState Key Laboratory of Engines, Tianjin University, Tianjin 300072, ChinaSchool of Engineering, RMIT University, Melbourne, VIC 3000, AustraliaShantui Construction Machinery CO., LTD, Jining 272000, ChinaState Key Laboratory of Engines, Tianjin University, Tianjin 300072, ChinaState Key Laboratory of Engines, Tianjin University, Tianjin 300072, ChinaState Key Laboratory of Engines, Tianjin University, Tianjin 300072, ChinaTo improve the performance of vehicle suspension, this paper proposes a semi-active vehicle suspension with a magnetorheological fluid (MRF) damper. We designed an optimized fuzzy skyhook controller with grey wolf optimizer (GWO) algorithm base on a new neuro-inverse model of the MRF damper. Because the inverse model of the MRF damper is difficult to establish directly, the Elman neural network was applied. The novelty of this study is the application of the new inverse model for semi-active vibration control and optimization of the semi-active suspension control method. The calculation results showed that the new inverse model can accurately calculate the required control current. The fuzzy skyhook control method optimized by the grey wolf optimizer (GWO) algorithm was established based on the inverse model to control the suspension vibration. The simulation results showed that the optimized fuzzy skyhook control method can simultaneously reduce the amplitude of vertical acceleration, suspension deflection, and tire dynamic load.https://www.mdpi.com/1996-1073/14/6/1674magnetorheological fluid damperinverse modelElman neural networkgrey wolf optimizersemi-active suspension |
| spellingShingle | Teng Ma Fengrong Bi Xu Wang Congfeng Tian Jiewei Lin Jie Wang Gejun Pang Optimized Fuzzy Skyhook Control for Semi-Active Vehicle Suspension with New Inverse Model of Magnetorheological Fluid Damper Energies magnetorheological fluid damper inverse model Elman neural network grey wolf optimizer semi-active suspension |
| title | Optimized Fuzzy Skyhook Control for Semi-Active Vehicle Suspension with New Inverse Model of Magnetorheological Fluid Damper |
| title_full | Optimized Fuzzy Skyhook Control for Semi-Active Vehicle Suspension with New Inverse Model of Magnetorheological Fluid Damper |
| title_fullStr | Optimized Fuzzy Skyhook Control for Semi-Active Vehicle Suspension with New Inverse Model of Magnetorheological Fluid Damper |
| title_full_unstemmed | Optimized Fuzzy Skyhook Control for Semi-Active Vehicle Suspension with New Inverse Model of Magnetorheological Fluid Damper |
| title_short | Optimized Fuzzy Skyhook Control for Semi-Active Vehicle Suspension with New Inverse Model of Magnetorheological Fluid Damper |
| title_sort | optimized fuzzy skyhook control for semi active vehicle suspension with new inverse model of magnetorheological fluid damper |
| topic | magnetorheological fluid damper inverse model Elman neural network grey wolf optimizer semi-active suspension |
| url | https://www.mdpi.com/1996-1073/14/6/1674 |
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