【摘要】 基于整车模型设计的主动悬架控制系统,控制器阶数往往较高.在保证主动悬架闭环系统性能的情况下如何尽可能地降低控制器的阶数,是有待解决的问题.本文首先建立汽车7自由度整车悬架模型.针对人体敏感的振动频率范围,设计汽车主动悬架H_∞控制器.在此基础上采用Hankel范数最优降阶法对所设计的高阶控制器进行降阶研究,与模态截取法、均衡截取法进行比较,结果显示Hankel范数最优降阶法能获得更好的降阶效果.对采用降阶和全阶控制器的主动悬架系统进行仿真的结果表明,Hankel范数最优降阶法在较大程度地降低控制器阶数的同时,闭环系统频域和时域特性没有明显降低且汽车乘坐舒适性良好.更多还原

【Abstract】 The active suspension control system based on the full-vehicle model is usually with a high-order controller. How to reduce the order of controller as low as possible and preserve the performance of closed-loop system is a problem which should be solved.In this paper,a state-space model for a 7-DOF full-vehicle active suspension system is firstly built.By considering the sensitivity of human to vibration,an H-infinity controller is then designed based on the model. The optimal Hankel-norm reduction(OHNR)method is utilized in the study of order-reduction for the designed high-order controller.Comparing with modal truncation method and balanced truncation method,it is shown that OHNR method can obtain a better order-reduction effect.Finally,the simulation results of the reduced-order and full-order active suspension systems demonstrate that the controller order can be considerably reduced by the OHNR method,and that the frequency domain and time domain performances of closed-loop system are not obviously degraded and the vehicle ride-comfort maintains well when the lower-order controller replaces the full-order controller.更多还原