Anti-disturbance iterative learning tracking control for space manipulators with repetitive reference trajectory

Purpose: This paper is concerned with the repetitive trajectory tracking control for space manipulators under model uncertainties and vibration disturbances. Design/methodology/approach: The model uncertainties and link vibration of manipulators will degrade the tracking performance of space manipulators; in this paper, a new hybrid control scheme that consists of a composite hierarchical anti-disturbance controller and an iterative learning controller is developed to solve this problem. Findings: The composite hierarchical controller can effectively attenuate model uncertainties and reject vibration disturbances, whereas the iterative learning controller is able to improve the tracking accuracy for repetitive reference trajectory. Originality/value: The proposed scheme compensates for the shortcomings of iterative learning control which can only deal with repetitive disturbances, ensuring the accuracy and repeatability of space manipulators under model uncertainties and random disturbances.