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Adaptive dynamic programming methods in control of wheeled mobile robot

Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The control problem of nonlinear systems is a demanding task that requires application of complex methods. The development of artificial intelligence methods in recent years has made it possible to design control systems able to adapt parameters to changing or unknown parameters of the controlled object or process. In the article, a new approach to the tracking control problem of a wheeled mobile robot is presented. It uses the newest methods of artificial intelligence, such as adaptive dynamic programming algorithms, in the tracking control task. The proposed tracking control system is compared to the neural control system and the PD controller in a problem of the mobile robot tracking control. Laboratory tests of the proposed control systems were advances performed using the wheeled mobile robot Pioneer 2-DX and the computational environment that makes real time control and data acquisition possible. The proposed tracking control systems are stable and do not require the stage of preliminary learning of neural networks.
Rocznik
Strony
837--851
Opis fizyczny
Bibliogr. 14 poz., rys. tab., wykr.
Twórcy
autor
autor
  • Rzeszów University of Technology 8 Powstancow Warszawy St., 35-959 Rzeszow, POLAND, zenhen@prz.edu.pl
Bibliografia
  • Barto A., Sutton R. and Anderson C. (1983): Neuronlike adaptive elements that can solve difficult learning problems. - IEEE Trans. On Systems, Man, and Cybernetics, vol.13, No.5, pp.834-846.
  • Barto A. and Sutton R. (1998): Reinforcement learning: an introduction. - Cambridge: MIT Press.
  • Giergiel J., Hendzel Z. and Zylski W. (2002): Modeling and control of wheeled mobile robots. (in Polish) - Warsaw: PWN.
  • Giergiel J. and Zylski W. (2005): Description of motion of a mobile robot by Maggie's equations. - J. of Theoretical and Applied Mechanics, vol.43, pp.511-521.
  • Hendzel Z. and Szuster M. (2010a): Discrete action dependant heuristic dynamic programming in wheeled mobile robot control. - Solid State Phenomena, vol.164, pp.419-424.
  • Hendzel Z. and Szuster M. (2010b): Discrete model-based adaptive critic designs in wheeled mobile robot control. - LNAI, vol.6114, pp.264-271.
  • Hendzel Z. and Szuster M. (2011): Discrete neural dynamic programming in wheeled mobile robot control. - Commun. Nonlinear Sci Numer Simulat, vol.16, No.5, pp.2355-2362.
  • Koshkouei A.J. and Zinober A.S. (2000): Sliding mode control of discrete-time systems. - J. Dyn. Sys., Meas., Control, vol.122, No.4, pp.793-802.
  • Lendaris G., Schultz L. and Shannon T. (2000): Adaptive critic design for intelligent steering and speed control of a 2-axle vehicle. - Proc. of the IEE INNSENNS International Joint Conference on Neural Networks, vol.3, pp.73-78.
  • Levis FL., Liu K. and Yesildirek A. (1995): Neural net robot controller with guaranteed tracking performance. - IEEE Transaction on Neural Networks, vol.6, No.3, pp.703-715.
  • Ortega R. and Spong M.W. (1989): Adaptive motion control of rigid robots: a tutorial. - Automatica, vol.25, No.6, pp.877-888.
  • Powell W.B. (2007): Approximate dynamic programming: Solving the curses of dimensionality. - Princeton: Willey-Interscience.
  • Prokhorov D. and Wunsch D. (1997): Adaptive critic designs. - IEEE Transactions on Neural Networks, vol.8, pp.997-1007.
  • Si J., Barto A.G., Powell W.B. and Wunsch D. (2004): Handbook of learning and approximate dynamic programming. - New York: IEEE Press, Willey-Interscience.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPZ5-0027-0033
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