Abstract
This paper addresses the Trajectory Tracking Problem for the Wheeled Mobile Robot, which is a nonlinear system. The trajectory tracking control problem is solved using the sliding mode control. In this paper the Evolution Strategy is investigated in order to obtain the best values for the sliding mode control law parameters. The performances of the control law with the optimum parameters are analyzed. The conclusions are based on the simulation results.
This work was supported by the Romanian High Education Scientific Research National Council (CNCSIS), under project PC ID-506.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Slotine, J., Li, W.: Applied Nonliner Control. Prentice Hall, New Jersey (1991)
Gao, W., Hung, J.: Variable structure control of nonlinear systems: A new approach. IEEE Transactions on Industrial Electronics 40, 45–55 (1993)
Utkin, V., Young, K.: Methods for constructing discontinuity planes in multidimensional variable structure systems. Automation and Remote Control 39, 1466–1470 (1978)
Dorling, C., Zinober, A.: Two approaches to hyperplane design in multivariable variable structure control systems. Int. Journal Control 44, 65–82 (1986)
Rechenberg, I.: Evolutionsstrategie: Optimierung Technischer Systeme nach Prinzipien der Biologischen Evolution. Frommann-Holzboog, Stuttgart (1973)
Schwefel, H.-P.: Numerische Optimierung von Computer-Modellen (PhD thesis) (1974); Reprinted by Birkhäuser (1977)
Holland, J.H.: Adaptation in natural and artificial systems. The University of Michigan Press, Ann Arbor (1975)
Koza, J.R.: Genetic Programming: On the Programming of Computers by Means of Natural Selection. MIT Press, Cambridge (1992)
Fogel, L.J., Owens, A.J., Walsh, M.J.: Artificial Intelligence through Simulated Evolution. John Wiley, NY (1966)
Beyer, H.-G., Schwefel, H.-P.: Evolution strategies - A comprehensive introduction. Natural Computing 1(1), 3–52 (2002)
Beyer, H.-G., Deb, K.: On self-adaptive features in real-parameter evolutionary algorithms. IEEE Transactions on Evolutionary Computation 5(3), 250–270 (2001)
Schwefel, H.-P.: Evolution and Optimum Seeking. Wiley, New York (1995)
Solea, R., Cernega, D.C.: Sliding Mode Control for Trajectory Tracking Problem - Performance Evaluation. In: Alippi, C., Polycarpou, M., Panayiotou, C., Ellinas, G. (eds.) ICANN 2009. LNCS, vol. 5769, pp. 865–874. Springer, Heidelberg (2009)
Lin, C.-L., Jan, H.-Y.: Application of evolution strategy in mixed H∞/H2 control for a linear brushless DC motor. Advanced Intelligent Mechatronics 1, 1–6 (2003) ISBN: 0-7803-7759-1
Iruthayarajan, M.W., Baskar, S.: Evolutionary algorithms based design of multivariable PID controller. Expert Syst. Appl. 36, 9159–9167 (2009)
Richter, R., Hofmann, W.: Evolution Strategies Applied to Controls on a Two Axis Robot Source. In: Reusch, B. (ed.) Fuzzy Days 1997. LNCS, vol. 1226, pp. 434–443. Springer, Heidelberg (1997) ISBN:3-540-62868-1
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Serbencu, A., Serbencu, A.E., Cernega, D.C. (2010). Evolutionary Strategies Used for the Mobile Robot Trajectory Tracking Control. In: Diamantaras, K., Duch, W., Iliadis, L.S. (eds) Artificial Neural Networks – ICANN 2010. ICANN 2010. Lecture Notes in Computer Science, vol 6353. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15822-3_36
Download citation
DOI: https://doi.org/10.1007/978-3-642-15822-3_36
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15821-6
Online ISBN: 978-3-642-15822-3
eBook Packages: Computer ScienceComputer Science (R0)