An iterative learning controller for nonholonomic mobile robots

We present an iterative learning controller that applies to nonholonomic mobile robots, as well as other systems that can be put in chained form. The learning algorithm exploits the fact that chained form systems are linear under piecewise-constant inputs. The proposed control scheme requires the execution of a small number of experiments to drive the system to the desired state infinite time, with nice convergence and robustness properties with respect to modeling inaccuracies as well as disturbances. To avoid the necessity of exactly reinitializing the system at each iteration, the basic method is modified so as to obtain a cyclic controller by which the system is cyclically steered through an arbitrary sequence of states. As a case study, a carlike mobile robot is considered. Both simulation and experimental results are reported to show the performance of the method.