Further results on advanced robust iterative learning control and modeling of robotic systems

Abstract

Recently, calculus of general order alpha is an element of R has attracted attention in scientific literature, where fractional operators are often used for control issues and the modeling of the dynamics of complex systems. In this work, some attention will be devoted to the problem of viscous friction in robotic joints. The calculus of general order and the calculus of variations are utilized for the modeling of viscous friction which is extended to the fractional derivative of the angular displacement. In addition, to solve the output tracking problem of a robotic manipulator with three DOFs with revolute joints in the presence of model uncertainties, robust advanced iterative learning control (AILC) is introduced. First, a feedback linearization procedure of a nonlinear robotic system is applied. Then, the proposed intelligent feedforward-feedback AILC algorithm is introduced. The convergence of the proposed AILC scheme is established in the time domain in detail. Finally, simulations on the given robotic arm system confirm the effectiveness of the robust AILC method.