Data‐driven iterative learning trajectory tracking control for wheeled mobile robot under constraint of velocity saturation

Considering the wheeled mobile robot (WMR) tracking problem with velocity saturation, we developed a data-driven iterative learning double loop control method constraints. First, authors designed an outer controller to provide virtual for inner according position and pose error of WMR kinematic model. Second, employed dynamic linearisation transform model into online along domain. Based on measured input output data model, identified parameters controller. The considered saturation constraints; adjusted online, providing effective solutions saltation constraint in process. Notably, only uses which not enables reliable trajectory tracking, but also avoids influence inaccurate identification processes performance. analysed algorithm's convergence theory, results show that errors position, angle can converge zero Finally, used simulation demonstrate effectiveness algorithm.