Stable iterative feedback tuning method for servo systems

This paper presents an Iterative Feedback Tuning (IFT) method to guarantee the control system stability throughout the iterations. The theoretical framework is based on the closed-loop stability testing in the context of coprime factor uncertainty for the controller, and it makes use of the small gain theorem for discrete-time systems. Bounds on the gain of the systems involved in the stability analysis are found from nonparametric models in frequency domain. A digitally simulated case study concerning the angular position control of a servo system is included to validate the new stable IFT method.

[1]  Claudia-Adina Dragos,et al.  Implementation and signal processing aspects of Iterative Regression Tuning , 2010, 2010 IEEE International Symposium on Industrial Electronics.

[2]  Bruce A. Francis,et al.  Optimal Sampled-Data Control Systems , 1996, Communications and Control Engineering Series.

[3]  Bo Wahlberg,et al.  Non-parametric methods for L2-gain estimation using iterative experiments , 2010, Autom..

[4]  Mato Baotic,et al.  Hybrid Theory-Based Time-Optimal Control of an Electronic Throttle , 2007, IEEE Transactions on Industrial Electronics.

[5]  Svante Gunnarsson,et al.  Iterative feedback tuning: theory and applications , 1998 .

[6]  Rik Pintelon,et al.  System Identification: A Frequency Domain Approach , 2012 .

[7]  Teresa Orlowska-Kowalska,et al.  Constrained Model Predictive Control of the Drive System With Mechanical Elasticity , 2009, IEEE Transactions on Industrial Electronics.

[8]  L.C. Kammer,et al.  Iterative feedback tuning with guaranteed stability , 1999, Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251).

[9]  József K. Tar,et al.  Fuzzy Control System Performance Enhancement by Iterative Learning Control , 2008, IEEE Transactions on Industrial Electronics.

[10]  Huibert Kwakernaak,et al.  Robust control and H∞-optimization - Tutorial paper , 1993, Autom..

[11]  Brian D. O. Anderson,et al.  Checking if controllers are stabilizing using closed-loop data , 2006, Proceedings of the 45th IEEE Conference on Decision and Control.

[12]  Sergio M. Savaresi,et al.  Virtual reference feedback tuning: a direct method for the design of feedback controllers , 2002, Autom..

[13]  Dominique Bonvin,et al.  Data-driven estimation of the infinity norm of a dynamical system , 2007, 2007 46th IEEE Conference on Decision and Control.

[14]  Marian P. Kazmierkowski,et al.  Control of Three-Level PWM Converter Applied to Variable-Speed-Type Turbines , 2009, IEEE Transactions on Industrial Electronics.

[15]  H. Bourles,et al.  A local small gain theorem for discrete-time systems , 1994, Proceedings of 1994 33rd IEEE Conference on Decision and Control.

[16]  Brian D. O. Anderson,et al.  Iterative minimization of H2 control performance criteria , 2008, Autom..

[17]  Diego Eckhard,et al.  Optimizing the convergence of data-based controller tuning , 2009 .

[18]  Robert R. Bitmead,et al.  Direct iterative tuning via spectral analysis , 2000, Autom..

[19]  N. K. Poulsen,et al.  Improving Convergence of Iterative Feedback Tuning , 2009 .

[20]  L. C. Kammer Stability assessment for cautious iterative controller tuning , 2004 .

[21]  Lennart Ljung,et al.  System Identification: Theory for the User , 1987 .