环卫车辆轨迹跟踪系统的无模型自适应迭代学习控制

针对环卫车辆周期重复性工作特点,考虑模型时变以及未知扰动问题,提出一种基于无模型自适应迭代学习的环卫车辆轨迹跟踪控制方法.首先,针对环卫车辆建立了两轮移动机器人的运动学模型,然后,给出带时变参数和非线性不确定项的迭代域下全格式动态线性化数据模型,引入时间差分估计算法,设计基于最优性能指标的轨迹跟踪无模型自适应迭代学习控...

Track tracking control of sanitation vehicle based on model-free adaptive iterative learning control

In this paper, a trajectory tracking control method for sanitation vehicles based on model-free adaptive iterative learning is proposed considering the problems of model time-varying and unknown disturbance aiming the periodic repetitive work characteristics. First of all, the kinematics model of two-wheeled mobile robot is built for the sanitation vehicle. Secondly, a full-format dynamic linearized data model with time-varying parameters and nonlinear uncertainties in the iterative domain is presented. Then a model-free adaptive iterative learning control (MFAILC) algorithm with time difference estimation algorithm for trajectory tracking based on the optimal performance index is designed. At the end, the simulation analysis was carried out. The research results show that the body angle of the trajectory tracking system of the sanitation vehicle decreases with the increase of iteration. Compared with the traditional iterative learning control algorithm, the improved method has slack conditional constraints and better robustness, and the control accuracy is improved.