A Study on Half-car Active Suspension Control by Combining EKF State Observation and Sliding Mode Algorithm
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摘要: 针对主动悬架控制可能面临的平顺性、悬架动挠度及车轮动载性能冲突,以及考虑参数不确定与外界干扰带来的鲁棒性问题,论文基于非线性滤波方法设计了滑模控制器以综合改善悬架性能;根据控制算法所需实时而准确的车辆状态信息需求,采用扩展卡尔曼滤波方法设计了状态观测器。分别进行随机路面激励、正弦路面激励和凸块路面激励仿真分析,结果显示所设计控制器具有良好的路面适应性,在不牺牲悬架动挠度的情况下,可以有效改善车辆平顺性及轮胎抓地力,有利于综合提升车辆的乘坐舒适性和操纵稳定性。Abstract: Due to the fact that there may be trade-offs among ride comfort, suspension deflection and tire deformation for the active suspension system, and considering the robustness of control system with parameter uncertainties and external disturbances, an active suspension controller based on nonlinear filtering method and the sliding mode variable structure control method was designed in order to comprehensively improve the suspension system performance. According to the previously established control algorithm, implementation of the control system requires real-time access to several key states, a state observer was proposed using the extended Kalman filter method. Subsequently, simulation schemes including random road excitation, sinusoidal road excitation and bump road excitation are carried out to validate the effectiveness of the entire control system. The results of the simulations show that, the proposed control system has good road adaptability, and can effectively improve ride comfort and road holding performance without sacrificing suspension deflection. Therefore, the proposed control system is beneficial to improve the ride quality and handling stability of vehicle.
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