On Analysis and Implementation of Iterative Learning Control

Many of the control systems used in factory production today are programmed to perform the same task repeatedly. In particular this is the case for industrial robots where the same motion is performed every time the same program is executed. An interesting observation, for the industrial robot, is that the error in the di erent iterations of the same exercise is highly repetitive. In the thesis Iterative Learning Control is applied to an industrial robot control system from ABB. Using Iterative Learning Control the tracking error on the motor side has been reduced without changing the internal structure or any parameters in the robot controller. The results from the experiments show that Iterative Learning Control can be used to successfully reduce the tracking error in an industrial robot control system. The implementation of the functions needed in the robot controller is described. By using a combination of already present functions in the system and software development the Iterative Learning Control method has been successfully applied to the commercial robot controller, S4C. The Iterative Learning Control method uses knowledge from previous exercises to improve the control in future executions of the same exercise. For the robot control case, this means remembering the error that was achieved in the previous iteration of the exercise and to change the input signal to the system based on this knowledge. A theory including analysis and synthesis for Iterative Learning Control is provided, and a starting point for a more general theory on iterative systems is given. A general discussion on how the Iterative Learning Control method can deal with repetitive and random disturbances is also included. Two of the given design algorithms are evaluated by experiments. The experiments show that the methods apply very well to the control of the ABB robot. The error reaches steady state levels, in fact the quantization level, already after 3 iterations with a model based synthesis approach. i Acknowledgments Climbing the stairs of life can sometimes be di cult and, for sure, some steps are bigger than others. To reach this step, now when the thesis is written, one of the most di cult steps in my life had to be conquered. This doesn't mean, of course, that is wasn't fun. In fact it was GREAT fun! Life has also taught me a lesson to remember: \Don't relax. It's not over until the fat lady sings..." First of all I would like to thank my supervisor, Dr. Svante Gunnarsson, and my industrial supervisor Dr. Torgny Brog ardh. This thesis had never been possible without all our fruitful discussions and all the valuable comments that I have received from you. Torgny read and gave me feedback on an early and a late version of the manuscript, these comments have improved the nal version considerably. I am also grateful to Prof. Lennart Ljung and Prof. Torkel Glad. The research environment that you have created in the group is unique. I am happy and proud to be a member of your sta . All the guys in the Automatic Control group are gratefully acknowledged. I especially thank Ulla, our secretary, for the administrative help and for always thinking beyond everyone else in the group1. Ulla, you are invaluable. A number of people have contributed to the work in di erent ways. Valur Einarsson read the manuscript and gave me many valuable comments and suggestions. Valur and Fredrik Tjarnstrom have also answered a lot of my questions and taken their time to listen to, and discuss, topics of my research. Thank you! M ans  Ostring has provided me with the controller in Chapter 7 and, also, with a lot of knowledge on the control of systems having exibilities (among other things). Thank you M ans (I owe you one). Soren Hansson is gratefully acknowledged for helping me with all the practical things in the lab. I also would like to thank Prof. Kevin Moore for sending me a preview of his survey article [Moo98]. The people at ABB Robotics have provided me with a new \family" in Vaster as. I am grateful to all of you. I send special thanks to Laila and Jappe for your great hospitality. I would also like to thank, Sta an, H akan, Fredrik, Bosse, Peter E, Steve, Geir, Daniel, Anders, Antonio, Stig, and all the rest of the people at ABB that have helped me during the work on this thesis. It would never have been possible without your help. 1At least when it comes to practical things. iii iv Acknowledgments This work was supported by ABB Robotics Products AB within NUTEK's Center of Excellence ISIS2, which is gratefully acknowledged. I also would like to thank my family, my Mother and my Father, my sister Lisbeth and her boyfriend Janne, and big-brother Mats. You have always taken cared of me and helped me to think of other things than work. Finally, I would like to thank Anna for all the love, support, and encouragement she has given me during the writing of this thesis. Ti amo! Il mio ❤ appartiene a te. Linkoping, October 1998 Mikael Norrlof 2Information Systems for Industrial Control and Supervision