Iterative Learning Tracking Control for a Vehicle-Manipulator System With Input Constraint

Abstract

In this study, the tracking control and saturation nonlinearities problems of a flexible mobile vehicle-manipulator with disturbance uncertainty are investigated. Based on the differential equations model, a novel iterative learning control (ILC) algorithm is designed, where two saturation functions and two hyperbolic tangent functions are utilized to deal with the actuator saturation constraint and an adaptive law is adopted to reduce the impact of disturbance uncertainty. With the ILC algorithm, the target of tracking control and vibration attenuation of the mobile manipulator can come true. Simulations are given to verify the effectiveness of designed control algorithm.INDEX TERMS Mobile vehicle-manipulator, saturation nonlinearities, tracking control, iterative learning control, disturbances.