A Practical Iterative Learning Path‐Following Control Of An Omni‐Directional Vehicle

Abstract

ABSTRACT A new practical iterative learning control (ILC) updating law is proposed to improve the path following accuracy for an omni‐directional autonomous mobile robot. The ILC scheme is applied as a feedforward controller to the existing feedback controller. By using the local symmetrical double‐integral of the feedback control signal of the previous iteration, the ILC updating law takes a simple form with only two design parameters: the learning gain and the range of local integration. Convergence analysis is presented together with a design procedure. Simulation results on a difficult maneuver are presented to illustrate the effectiveness of the proposed simple and yet practical scheme. The simulation is based on the model of a novel robotic platform, the Utah State University (USU) Omni‐Directional Vehicle (ODV), which uses multiple “smart wheels,” whose speed and direction can be independently controlled through dedicated processors for each wheel.