Open closed-loop PDmi/PD type ILC control of Neuroarm robotic system

Abstract

In this paper, an advanced iterative learning control algorithm (ILC) is introduced in order to solve the output tracking problem of a robotic manipulator with three degrees of freedom. Iterative fractional order PDμ type control is located in feedforward path, and combined together with classical feedback PD controller. Fractional derivative μ provides additional flexibility in adjusting the output performances. Parameters of the feedback controller are derived using a modern approach which takes into consideration both performance and robustness characteristics of the closed loop system. This is achieved by a suitable selection of only one adjustable parameter. Mathematical model of robotic manipulator is derived together with actuator dynamics, and it is shown that in the presence of high gear ratio the nonlinear effects can be neglected, and only linear model can be observed. The efficiency of the proposed control algorithm is demonstrated by simulations, in which robotic arm needs to follow desired trajectory given in joint space. Excellent tracking performances are achieved only after few iterations.