Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 30761
Sensor Optimisation via H∞ Applied to a MAGLEV Suspension System

Authors: Konstantinos Michail, Argyrios Zolotas, Roger Goodall, John Pearson

Abstract:

In this paper a systematic method via H∞ control design is proposed to select a sensor set that satisfies a number of input criteria for a MAGLEV suspension system. The proposed method recovers a number of optimised controllers for each possible sensor set that satisfies the performance and constraint criteria using evolutionary algorithms.

Keywords: Genetic Algorithms, H-infinity, Sensor optimisation, MAGLEV vehicles

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1058909

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1120

References:


[1] Coello C.A.C. Theoretical and numerical constraint-handling techniques used with evolutionary algorithms: A survey of the state of the art. Computer Methods in Applied Mechanics and Engineering, 191(11- 12):1245-1287, 2002. Compilation and indexing terms, Copyright 2007 Elsevier Inc. All rights reserved.
[2] N. V. Dakev, J. F. Whidborne, A. J. Chipperfield, and P. J. Flemings. Evolutionary h infinity design of an electromagnetic suspension control system for a maglev vehicle. Proceedings of the Institution of Mechanical Engineers.Part I, Journal of Systems & Control Engineering, 211(5):345-355, 1997. Compilation and indexing terms, Copyright 2007 Elsevier Inc. All rights reserved.
[3] Kalyanmoy Deb. Multi-objective Optimization using Evolutionary Algorithms. John Wiley & sons Ltd, 2001.
[4] Kalyanmoy Deb, Amrit Pratap, Sameer Agarwal, and T. Meyarivan. A fast and elitist multiobjective genetic algorithm: Nsga-ii. IEEE Transactions on Evolutionary Computation, 6(2):182-197, 2002. Compilation and indexing terms, Copyright 2007 Elsevier Inc. All rights reserved.
[5] J. Dreo, P. Siarry, A. Petrowski, and E. Taillard. Metaheuritics for Hard Optimization. Springer-Verlg Berlin Heidelberg, New York, 2006.
[6] P. J. Fleming and R. C. Purshouse. Evolutionary algorithms in control systems engineering: A survey. Control Engineering Practice, 10(11):1223-1241, 2002. Compilation and indexing terms, Copyright 2006 Elsevier Inc. All rights reserved.
[7] R. M. Goodall. Dynamic characteristics in the design of maglev suspensions. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 208(1):33-41, 1994. Compilation and indexing terms, Copyright 2007 Elsevier Inc. All rights reserved.
[8] R. M. Goodall. Dynamics and control requirements for ems maglev suspensions. In Proceedings on international conference on Maglev, pages 926-934, Oct 2004.
[9] R. M. Goodall. The theory of electromagnetic levitation. Physics in Technology, Vol. 16(No 5):pp 207-213, Sept 1985.
[10] J. A. Joines and C. R. Houck. On the use of non-stationary penalty functions to solve nonlinear constrained optimization problems with ga-s. In Evolutionary Computation, 1994. IEEE World Congress on Computational Intelligence., Proceedings of the First IEEE Conference on, pages 579-584 vol.2, 1994.
[11] Hyung-Woo Lee, Ki-Chan Kim, and Ju Lee. Review of maglev train technologies. IEEE Transactions on Magnetics, 42(7):1917-1925, 2006. Compilation and indexing terms, Copyright 2007 Elsevier Inc. All rights reserved.
[12] S. Skogestad and I. Postlethwaite. Multivariable Feedback Control Analysis and Design. John Wiley & Sons,Ltd, 2005.