Relaxing Convergence Constraints in Local Priority Hysteresis Switching Logic
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32799
Relaxing Convergence Constraints in Local Priority Hysteresis Switching Logic

Authors: Mubarak Alhajri

Abstract:

This paper addresses certain inherent limitations of local priority hysteresis switching logic. Our main result establishes that under persistent excitation assumption, it is possible to relax constraints requiring strict positivity of local priority and hysteresis switching constants. Relaxing these constraints allows the adaptive system to reach optimality which implies the performance improvement. The unconstrained local priority hysteresis switching logic is examined and conditions for global convergence are derived.

Keywords: Adaptive control, convergence, hysteresis constant, hysteresis switching.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1129237

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 839

References:


[1] M. Alhajri and M. Safonov. Setting the hysteresis constant to zero in adaptive switching control. In American Control Conference (ACC), pages 3542–3546. IEEE, 2011.
[2] M. Alharashani. Relaxing convergence assumptions for continuous adaptive control. PhD thesis, University of Southern California, 2010.
[3] B. D. O. Anderson. Exponential Stability of Linear Equations Arising in Adaptive Identification. IEEE Transactions on Automatic Control, 22:83–88, 1977.
[4] K. J. Astrom and T. Bohlin. Numerical identification of linear dynamic systems from normal operating records. In Theory of Self-Adaptive Control Systems, page 96, 1966.
[5] K. J. A˚ stro¨m and B. Wittenmark. Adaptive control. Courier Corporation, 2013.
[6] G. Battistelli, J. A. Hespanha, E. Mosca, and P. Tesi. Unfalsified adaptive switching supervisory control of time varying systems. In Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference. CDC/CCC 2009. Proceedings of the 48th IEEE Conference on, pages 805–810. IEEE, 2009.
[7] D. Bertsekas. Nonlinear programming. 1999. Athena Scientific, Belmont, MA, 1999.
[8] D. P. Bertsekas. Nonlinear Programming. Athena Scientific Belmont, MA, 1999.
[9] R. Bitmead. Persistence of excitation conditions and the convergence of adaptive schemes. IEEE Transactions on Information Theory, 30(2):183–191, 1984.
[10] S. Boyd and S. S. Sastry. Necessary and Sufficient Conditions for Parameter Convergence in Adaptive Control. Automatica, 22(6):629–639, 1986.
[11] Z. Han and K. S. Narendra. New concepts in adaptive control using multiple models. Automatic Control, IEEE Transactions on, 57(1):78–89, 2012.
[12] J. Hespanha, D. Liberzon, and A. Morse. Hysteresis-based switching algorithms for supervisory control of uncertain systems* 1. Automatica, 39(2):263–272, 2003.
[13] J. Hespanha, D. Liberzon, A. S. Morse, B. D. O. Anderson, T. S. Brinsmead, and F. D. Bruyne. Multiple model adaptive control. Part 2: Switching. International Journal of Robust and Nonlinear Control, 11(5):479–496, 2001.
[14] A. Morse. Towards a unified theory of parameter adaptive control. II. Certainty equivalence and implicit tuning. IEEE Transactions on Automatic Control, 37(1):15–29, 1992.
[15] A. S. Morse. Supervisory control of families of linear set-point controllers — Part I: Exact matching. Automatic Control, IEEE Transactions on, 41(10):1413–1431, Oct 1996.
[16] A. S. Morse. Supervisory control of families of linear set-point controllers — Part II: Robustness. IEEE Transactions on Automatic Control, 42(11):1500–1515, Nov 1997.
[17] A. S. Morse, D. Q. Mayne, and G. C. Goodwin. Applications of hysteresis switching in parameter adaptive control. IEEE Transactions on Automatic Control, 37(9):1343–1354, Sep 1992.
[18] J. R. Munkres. Topology: A First Course. Prentice-Hall, Englewood Cliffs, NJ, 1975.
[19] K. Narendra and A. Annaswamy. Persistent excitation in adaptive systems. International Journal of Control, 45(1):127–160, 1987.
[20] S. V. Patil, Y.-C. Sung, and M. G. Safonov. Unfalsified adaptive control with reset and bumpless transfer. In Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on, pages 1264–1270. IEEE, 2014.
[21] P. Rosa and C. Silvestre. Multiple-model adaptive control using set-valued observers. International Journal of Robust and Nonlinear Control, 24(16):2490–2511, 2014.
[22] K. S. Sajjanshetty and M. G. Safonov. Unfalsified adaptive control: Multi-objective cost-detectable cost functions. In Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on, pages 1283–1288. IEEE, 2014.
[23] M. Stefanovic and M. Safonov. Safe adaptive switching control: Stability and convergence. Automatic Control, IEEE Transactions on, 53(9):2012–2021, Oct. 2008.
[24] M. Vaezi, A. Izadian, and M. Deldar. Adaptive control of a hydraulic wind power system using multiple models. In Industrial Electronics Society, IECON 2014-40th Annual Conference of the IEEE, 2014.