针对自动泊车系统,提出了无模型自适应控制(Model-free adaptive control, MFAC)方案。控制方案的设计仅利用泊车系统的前轮转角输入数据和车身角输出数据,不包含车辆模型信息。因此,针对不同车型的自动泊车系统,该方案均能实现无模型自适应控制。为了改善期望轨迹的坐标跟踪误差,进一步提出基于坐标补偿的无模型自适应控制方案,该方案由控制算法、参数估计算法、参数重置算法和坐标补偿算法构成。针对不同车型不同泊车速度的仿真结果表明,基于坐标补偿的MFAC 方案和原型MFAC方案均能较好地完成自动泊车过程,且基于坐标补偿的MFAC方案相比原型MFAC方案和PID控制方案,在轨迹坐标和车身角等方面均具有更小的跟踪误差和更快的响应速度。
In this paper, a model-free adaptive control (MFAC) scheme is proposed for automatic car parking systems. The design of the proposed scheme only depends on the steering angle and the orientation angle of the car, and it does not involve any model information of the car. Therefore, the MFAC based automatic parking system is applicable to different kinds of cars. In order to further reduce the desired trajectory coordinate tracking error, a modified MFAC scheme with coordinates compensation is also proposed, which consists of a control algorithm, a parameter estimation algorithm, a parameter reset algorithm, and a coordinates compensation algorithm. A simulation comparison among MFAC scheme with coordinates compensation, prototype MFAC scheme, and PID control algorithm is given for different kinds of cars with different parking speeds. It is shown that both the prototype MFAC scheme and the MFAC scheme with coordinates compensation can better finish the automatic parking process, and the MFAC scheme with coordinates compensation has smaller tracking errors and more rapid responses to the orientation angle of the car and the trajectory coordinates than the prototype MFAC and PID schemes.