Using Genetic Algorithms in Closed Loop Identification of the Systems with Variable Structure Controller

Authors: O.M. Mohamed vall, M. Radhi

Abstract:

This work presents a recursive identification algorithm. This algorithm relates to the identification of closed loop system with Variable Structure Controller. The approach suggested includes two stages. In the first stage a genetic algorithm is used to obtain the parameters of switching function which gives a control signal rich in commutations (i.e. a control signal whose spectral characteristics are closest possible to those of a white noise signal). The second stage consists in the identification of the system parameters by the instrumental variable method and using the optimal switching function parameters obtained with the genetic algorithm. In order to test the validity of this algorithm a simulation example is presented.

Keywords: Closed loop identification, variable structure controller, pseud-random binary sequence, genetic algorithms.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1076686

References:

[1] Jonh Y. Hung, "Variable structure control: A survey", IEEE Transactions Industrials Electronics, vol. 40, n┬░ 1, Feb 1993, p. 2-22.
[2] Feng Zhao and Vadim I. Utkin, "Adaptive Simulation and Control of Variable Structure Control Systems in Sliding Regimes", Automatica, vol. 32, n┬░ 7, Feb 1996, p. 1037-1042.
[3] V.I. Utkin, "Sliding Mode Control Design Principles and Applications to Electric Drives", IEEE Transactions Industrials Electronics, vol. 40, n┬░ 1, Feb 1993, p. 23-36.
[4] Lennart Ljung, "System Identification Toolbox for use with Matlab", User-s Guide Version 5. Novembre 2000.
[5] Forssell U and L. Ljung, "Closed-loop identification revisited", Automatica 35(7), 1215-1241. 1999.
[6] Van den Hof, P.M.J, "Closed-loop issues in system identification", Annual Reviews in Control 22, 173-186, 1998.
[7] Ljung and U. Forssell, "A alternative motivation for the indirect approach to closed loop identification". IEEE Trans. Automatic Control, AC-44(11):2206-2209, Nov 1999.
[8] Forssell U and C. T. Chou, "Efficiency of prediction error and instrumental variable methods for closed-loop identification", Technical Report LiTH-ISY-R-2015. Dept of EE. Linköping University. S-581 83 Linköping, Sweden, 1998.
[9] M. Wang, N.F. Thornhill and B. Huang, "Closed-loop identification based on quantization", 15th Triennial World Congress, Barcelona, Spain, 2002.
[10] F. Herrera, M. Lozano, J.L. Verdegay, "Tackling Real-Coded Genetic Algorithms: Operators and tools for the Behaviour Analysis", Artificial Intelligence Review 12, 1998, p. 265-319.