【摘要】 考虑到智能车辆在不同工况下表现出不同的系统特性,设计了由线性二次型最优控制律和利用模糊逻辑推理得到的模糊控制律组成的混合切换控制器。当偏差和偏差变化率较小时(小角度转弯),假设系统特性固定不变,切换到最优控制律;而在偏差和偏差变化率较大时(大角度转弯),车辆具有强非线性、时变、耦合和参数不确定性等特性,切换到模糊控制律。采用ADAMS和Matlab/Simulink联合控制仿真的方法对该智能车辆的横向控制算法进行仿真,并通过试验验证。仿真和试验结果表明:该横向控制器可保证智能车辆在路径跟踪过程中的准确性和平稳性。更多还原

【Abstract】 Considering the different dynamic performances of intelligent vehicle under various conditions,mixed switching lateral controller was designed that consists of optimal control law obtained through the linear quadratic form optimal track control theory and fuzzy control law obtained by fuzzy logic analysis.When the error and error rate was small,the steering controller was switched to optimal control law.When the error and error rate was greater than or equal to the threshold,the fuzzy control law was selected.Simulative researched on the lateral control algorithm of intelligent vehicle using ADAMS and Matlab / Simulink co-simulation control,and tested by experimental.Simulation and experimental results showed that the unmanned vehicle controlled by the proposed algorithm could track the reference paths under various conditions accurately and riding quality.更多还原