| The Model Reference Adaptive Fuzzy Control for the Vehicle Semi-Active Suspension |
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| 作者姓名： | 管继富 侯朝桢 顾亮 武云鹏 |
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| 作者单位： | [1]DepartmentofAutomaticControl,SchoolofInformationScienceandTechnology,BeijingInstituteofTechnology,Beijing100081,China [2]SchoolofMechanicalandVehicularEngineering,BeijingInstituteofTechnology,Beijing100081,China |
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| 基金项目： | theMinisterialLevelAdvancedResearchFoundation( 2 0 0 10 45 3 ) |
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| 摘 要： | The LQG control system is employed as vehicle suspension‘ s optimal target system, which has an adaptive ability to the road conditions and vehicle speed in a limited bandwidth. In order to keep the optimal performances when the suspension parameters change, a model reference adaptive fuzzy control (MRAFC) strategy is presented. The LQG control system serves as the reference model in the MRAFC system. The simulation results indicate that the presented MRAFC system can adapt to the parameters variation of vehicle suspension and track the optimality of the LQG control system, the presented vehicle suspension MRAFC system has the ability to adapt to road conditions and suspension parameters change.
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| 关 键 词： | 自适应模糊控制 最佳目标系统 LQG控制系统 车辆动力学 半能动悬吊 车速 |
| 收稿时间： | 2003/6/17 0:00:00 |
The Model Reference Adaptive Fuzzy Control for the Vehicle Semi-Active Suspension |
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| GUAN Ji-fu,HOU Chao-zhen,GU Liang and WU Yun-peng.The Model Reference Adaptive Fuzzy Control for the Vehicle Semi-Active Suspension[J].Journal of Beijing Institute of Technology,2003,12(4):342-346. |
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| Authors: | GUAN Ji-fu HOU Chao-zhen GU Liang and WU Yun-peng |
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| Affiliation: | 1. Department of Automatic Control, School of Information Science and Technology, Beijing Institute of Technology, Beijing 100081, China
2. School of Mechanical and Vehicular Engineering, Beijing Institute of Technology, Beijing 100081, China |
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| Abstract: | The LQG control system is employed as vehicle suspension's optimal target system, which has an adaptive ability to the road conditions and vehicle speed in a limited bandwidth. In order to keep the optimal performances when the suspension parameters change, a model reference adaptive fuzzy control (MRAFC) strategy is presented. The LQG control system serves as the reference model in the MRAFC system. The simulation results indicate that the presented MRAFC system can adapt to the parameters variation of vehicle suspension and track the optimality of the LQG control system, the presented vehicle suspension MRAFC system has the ability to adapt to road conditions and suspension parameters change. |
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| Keywords: | semi-active suspension LQG control MRAFC control adaptive control |
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