A novel iterative learning control (ILC) for perspective dynamic system (PDS) is designed and illustrated in detail in this article to overcome the uncertainties in path tracking of mobile service robots. PDS, which transmits the motion information of mobile service robots to image planes (such as a camera), provides a good control theoretical framework to estimate the robot motion problem. The proposed ILC algorithm is applied in accordance with the observed motion information to increase the robustness of the system in path tracking. The convergence of the presented learning algorithm is derived as the number of iterations tends to infinity under a specified condition. Simulation results show that the designed framework performs efficiently and satisfies the requirements of trajectory precision for path tracking of mobile service robots.

中文翻译：

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不确定性透视动态系统中服务机器人路径跟踪的迭代学习控制

为了克服移动服务机器人路径跟踪的不确定性，本文设计并详细说明了一种新颖的透视动态系统（PDS）迭代学习控制（ILC）。PDS 将移动服务机器人的运动信息传输到图像平面（如相机），为估计机器人运动问题提供了良好的控制理论框架。根据观察到的运动信息应用所提出的 ILC 算法，以增加系统在路径跟踪中的鲁棒性。当迭代次数在指定条件下趋于无穷大时，可以得出所提出的学习算法的收敛性。仿真结果表明，所设计的框架高效运行，满足移动服务机器人路径跟踪对轨迹精度的要求。