Abstract
This paper proposes an iterative learning controller (ILC) under the alignment condition for trajectory tracking of a parallel Delta robot, that performs various repetitive tasks for palletization. Motivated by the high cadence of our application that leads to significant coupling effects, where the traditional PD/PID fail to satisfy the requirements performances. A PD-type ILC is combined with a PD controller in order to enhance the performance through iterations during the whole operation interval. The traditional resetting condition is replaced by the practical alignment condition, then the convergence of the tracking error is derived based on the Lyapunov’s theory. We definitely point out that the position and velocity errors decrease as the number of iterations increases. Experiments are carried out to demonstrate the effectiveness of the proposed controller.
Zusammenfassung
In diesem Beitrag wird ein iterativ lernender Regler für die Trajektorienverfolgung eines parallelen Delta-Roboters unter Gleichlaufbedingungen vorgeschlagen, der verschiedene wiederkehrende Palettierungsaufgaben ausführt. Durch den schnellen, zu signifikanten Kopplungen führenden, Rhythmus dieser Anwendung erwiesen sich übliche PD/PID-Regelungen als ungeeignet, um die Güteforderungen zu erfüllen. Um die Güte der Regelung über den gesamten Betriebszyklus zu steigern, wird eine iterativ lernende Regelung mit einem PD-Regler kombiniert. Die übliche Rücksetzbedingung wird zunächst durch die praktische Annäherungsbedingung ersetzt, anschließend wird die Konvergenz des Folgefehlers auf Basis der Ljapunow-Theorie gezeigt. Es statt Eindeutig wird gezeigt, dass der Positions- und Geschwindigkeitsfehler mit der Zahl der Iterationen abnimmt. Anhand von Experimenten wird die Tauglichkeit der vorgeschlagenen Regelung demonstriert.
About the authors
Chems Eddine Boudjedir received the engineer degree in Automatic Control from Ecole Nationale Polytechnique of Algeria in 2015. He is pursuing his PhD in the Automatic department of Ecole Nationale Polytechnique (ENP), Algiers, Algeria. His research interests include iterative learning control, time-delay control and robotics.
Mohamed Bouri graduated in Electrical Engineering in 1992 and obtained his PhD degree in 1997 in Industrial Automation at INSA LYON, France. He joined EPFL, Ecole Polytechnique Federal de Lausanne in 1997 and since 2005, he is a group leader of Rehabilitation and Assistive Robotics in the LSRO and lecturer of Robotics and Industrial Robotics. He is mainly active in the field of robot control, automation and robot design for medical and industrial applications. He has strong references with the development of many industrialized robots such as Hita machine (Willemein Macodel), Delta Direct Drive (Bosch Packaging Technology), MotionMaker and WalkTrainer (Swortec), 5 Axis Polishing Delta (Unitechnnologies).
Prof. Djamel Boukhetala was born in Algeria, on September 24, 1964. He received the Magister degree and the PhD degree in Automatic Control from the Ecole Nationale Polytechnique, Algeria in 1993 and 2002 respectively. From 1996 to 1999 he was the head of the Department of Automatic Control. From 2005 to 2013 he was the Director of the Control Process Laboratory and from 2010 to date he is the Director of Postgraduate Studies and Scientific Research at Ecole Nationale Polytechnique of Algeria. His research interests are decentralized control, non linear control, fuzzy control and artificial neural networks control applied to robotics, industrial process and Smart Grids.
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