Learning Control of Robot Manipulators 1

Learning control encompasses a class of control algorithms for programmable machines such as robots which attain, through an iterative process, the motor dexterity that enables the machine to execute complex tasks. In this paper we discuss the use of function identiication and adaptive control algorithms in learning controllers for robot manipulators. In particular, we discuss the similarities and diierences between betterment learning schemes, repetitive controllers and adap-tive learning schemes based on integral transforms. The stability and convergence properties of adaptive learning algorithms based on integral transforms are highlighted and experimental results illustrating some of these properties are presented.