Conference article

Optimal Robot Control Using Modelica and Optimica

Martin Hast
Department of Automatic Control, LTH, Lund University, Sweden

Johan Åkesson
Department of Automatic Control, LTH, Lund University, Sweden \ Modelon AB, Sweden

Anders Robersson
Department of Automatic Control, LTH, Lund University, Sweden

Download articlehttp://dx.doi.org/10.3384/ecp09430089

Published in: Proceedings of the 7th International Modelica Conference; Como; Italy; 20-22 September 2009

Linköping Electronic Conference Proceedings 43:87, s. 740-747

Show more +

Published: 2009-12-29

ISBN: 978-91-7393-513-5

ISSN: 1650-3686 (print), 1650-3740 (online)

Abstract

In this paper; Modelica along with Optimica is used to formulate and solve a minimum time optimization problem. The problem concerns the traversal of a given path with a robot in as short time as possible under input constraints. Several problem reformulations; increasing the chance of finding optimal solutions; are discussed. This paper also discusses the use of these optimal solutions for control of industrial robots. A control structure; in which the optimal trajectories are essential; is used on an ABB IRB140B to ensure robustness for model errors and disturbances.

Keywords

Modelica; Optimica; Optimization; Robot Control

References

[1] ABB. ABB Home Page; 2009. http://www.abb.com/.

[2] Johan Åkesson. Tools and Languages for Optimization of Large-Scale Systems. PhD thesis; Department of Automatic Control; Lund University; Sweden; November 2007. ISRN LUTFD2/TFRT- -1081- -SE.

[3] Johan Åkesson. Optimica—an extension of modelica supporting dynamic optimization. In In 6th International Modelica Conference 2008. Modelica Association; March 2008.

[4] Johan Åkesson; Tove Bergdahl; Magnus Gäfvert; and Hubertus Tummescheit. Modeling and Optimization with Modelica and Optimica Using the JModelica.org Open Source Platform. In Proceedings of the 7th International Modelica Conference 2009. Modelica Association; September 2009.

[5] AMPL - A Modeling Language for Mathematical Programming. AMPL Home Page; 2009. http://www.ampl.com/.

[6] L.T. Biegler; A.M. Cervantes; and A Wächter. Advances in simultaneous strategies for dynamic optimization. Chemical Engineering Science; 57:575–593; 2002. doi: 10.1016/S0009-2509(01)00376-1

[7] Ola Dahl. Path Constrained Robot Control. PhD thesis; Department of Automatic Control; Lund University; Sweden; April 1992. ISRN LUTFD2/TFRT- -1038- -SE.

[8] Fredrik Eriksson and Marcus Welander. Haptic interface for a contact force controlled robot. Master’s Thesis ISRN LUTFD2/TFRT- -5837- - SE; Department of Automatic Control; Lund University; Sweden; May 2009.

[9] Python Software Foundation. Python Programming Language – Official Website; 2009. http://www.python.org/.

[10] IPOPT - Interior Point OPTimizer. IPOPT HomePage; 2009. https://projects.coinor.org/Ipopt.

[11] Modelon AB. JModelica Home Page; 2009. http://www.jmodelica.org.

[12] Mark W. Spong; Seth Hutchinson; and M.Vidyasagar. Robot Modeling and Control. John Wiley & Sons; Inc; 2006.

[13] Andreas Wächter and Lorenz T. Biegler. On the implementation of an interior-point filter line- search algorithm for large-scale nonlinear programming. Mathematical Programming; 106(1):25–58; 2006. doi: 10.1007/s10107-004-0559-y.

Citations in Crossref