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Mathematical Problems in Engineering
Volume 2015 (2015), Article ID 187948, 13 pages
Research Article

Iterative Learning Control with Desired Gravity Compensation under Saturation for a Robotic Machining Manipulator

School of Mechanical, Aeronautical and Industrial Engineering, University of the Witwatersrand, 1 Jan Smuts Avenue, Private Bag 03, Johannesburg WITS2050, South Africa

Received 10 September 2015; Revised 23 November 2015; Accepted 6 December 2015

Academic Editor: Yan-Jun Liu

Copyright © 2015 Horacio Ernesto and Jimoh O. Pedro. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper proposes the design of a hybrid iterative learning controller for a four-degree-of-freedom (DOF) robotic machining manipulator (RMM). It combines a nonlinear saturated proportional + integral + derivative (PID) control with desired gravity compensation () and proportional + derivative- (PD-) based iterative learning control (ILC). The control is the primary component that maintains the local stability of the entire RMM system and the PDILC component provides robustness to parameter variations and uncertainties in the robot dynamics. Global asymptotic stability of the proposed control algorithm is conducted using Lyapunov direct method and LaSalles invariance principle. Simulation results show the effectiveness and robustness of the proposed hybrid iterative learning controller. It is also shown that the proposed controller achieved better tracking performances compared to conventional feedback controller.