Self-Tuning Robot Control Based on Subspace Identification

Authors: Mathias Marquardt, Peter Dünow, Sandra Baßler

Abstract:

The paper describes the use of subspace based identification methods for auto tuning of a state space control system. The plant is an unstable but self balancing transport robot. Because of the unstable character of the process it has to be identified from closed loop input-output data. Based on the identified model a state space controller combined with an observer is calculated. The subspace identification algorithm and the controller design procedure is combined to a auto tuning method. The capability of the approach was verified in a simulation experiments under different process conditions.

Keywords: Auto tuning, balanced robot, closed loop identification, subspace identification.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1125739

References:

[1] Larimore, W.E., Canonical Variate Analysis in Identification, Filtering and Adaptive Control, Proceedings of the 29th Conference on Decision and Control, Hawaii, 1990
[2] Peloubet, R.P. and Haller, R.L. and Bolding, R.M., On-Line Adaptive Control of Unstable Aircraft Wing Flutter, Proceedings of the 29th Conference on Decision and Control, Hawaii, 1990
[3] Verheagen, M. and Dewilde, P., Subspace model identification, Part I: The output-error state space model identification class of algorithms, Int. J. Control, Vol. 56, 1187-1210, 1992
[4] Van Overschee, P. and DeMoor, B., Subspace Identification of Linear Systems: Theory, Implementation, Application, Kluwer Academic Publischers, 1996
[5] Ljung, L. and McKelvey, T., Subspace identification from closed loop data, Signal Processing 52, 209-215, 1996
[6] Ljung, L., System Identification: Theory for the user, second ed., Prentice-Hall, Inc., 1999
[7] Larimore, W.E., Automated Multivariable System Identification and Industrial Applications, Proceedings of the American Control Conference, San Diego, California, 1999
[8] Qin, S.J. and Ljung, L., Closed-loop Subspace Identification with Innovation Estimation, Proceedings of SYSID 2003, Rotterdam, 2003
[9] Chiuso, A., The role of Vector Auto Regressive Modeling in Predictor-Based Subspace Identification, Automatica, Vol. 43, No. 6, 2007
[10] de Korte, R., Subspace-Based Identification Techniques for a ‘Smart’ Wind Turbine Rotor Blade, Delft University of Technology, M.Sc. Thesis, 2009
[11] Marquardt, M., D¨unow, P. and Baßler, S., Application of Subspace State-space Identification Methods on Actuated Multibody Systems, 20th International Conference on Methods and Models in Automation and Robotics (MMAR), Misdroy, Poland, 2015