Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
Differential games are a combination of game theory and optimum control methods. Their solutions are based on Bellman's principle of optimality. In this paper, the zero-sum differential game theory has been used for the purposes of controlling a mechatronic object: a single-link manipulator. In this case, analytical solutions are unavailable, thus approximate solutions were used. Two approximation methods were compared with the use of numerical simulations and selected quality indicators. The results confirm previous assumptions and the connection between the differential game theory and H∞ control problems.
Rocznik
Tom
Strony
867--878
Opis fizyczny
Bibliogr. 14 poz., rys., tab., wykr.
Twórcy
autor
- Faculty of Mechanical Engineering and Aeronautics, Rzeszów University of Technology, ul. Powstańców Warszawy 8, 35-959 Rzeszów, Poland
autor
- Faculty of Mechanical Engineering and Aeronautics, Rzeszów University of Technology, ul. Powstańców Warszawy 8, 35-959 Rzeszów, Poland
Bibliografia
- [1] Abu-Khalaf M., Huang J. and Lewis Frank. L. (2006): Nonlinear H2 / H∞ Constrained Feedback Control. – London: Springer.
- [2] Johnson Marcus A. (2011): Differential game-based control methods for uncertain continuous-time nonlinear systems. – Phd Thesis, University of Florida.
- [3] Starr A.W. and Ho Y.C. (1969): Nonzero-sum differential games. – Journal of Optimization Theory and Applications, vol.3, No.3, pp.184–206.
- [4] Willems Jan C. (1972): Dissipative dynamical systems part I: General theory. – Archive for Rational Mechanics and Analysis, vol.45, No.5, pp.321–351.
- [5] Van der Schaft A.J. (1992): L2-gain analysis of nonlinear systems and nonlinear state feedback H∞ control. – IEEE Trans. on Autom. Control, vol.37, No.6, pp.770-784 1992.
- [6] Hendzel Z. and Penar P. (2016): The used of differential game theory in the control wheeled mobile robot motor (in Polish). – Przegląd Mechaniczny, vol.75, No.1–2, pp.25–31.
- [7] Kyriakos G. Vamvoudakis and Lewis Frank L. (2012): Online solution of nonlinear two-player zero-sum games using synchronous policy iteration. – International Journal of Robust and Nonlinear Control, vol.22, pp.1460–1483.
- [8] Huai-Ning Wu and Biao Luo (2012): Neural network based online simultaneous policy update algorithm for solving the HJI equation in nonlinear H∞ control. – IEEE Transactions Neural Networks and Learning Systems, vol.23, No.12, pp.1884–1895.
- [9] Yasini S., Naghibi Sistani M.B. and Karimpour A. (2014): Policy Iteration Algorithm Based on Experience Replay to Solve H∞ Control Problem of Partially Unknown Nonlinear Systems. – Int. J. Control. Autom. Syst., European Control Conference.
- [10] Hendzel. and Gierlak P. (2011): Control of Wheeled and Manipulators Robots (in Polish). – Rzeszow: OWPRz.
- [11] Fei-Yue Wang, Zhang H. and Liu D. (2009): Adaptive dynamic programming: An introduction. – IEEE Computational Intelligence Magazine, vol.4, No.2, pp.39–47.
- [12] Shankar S. and Bodson M. (1989): Adaptive Control. Stability, Convergence and Robustness. – New Jersey: Prentice Hall.
- [13] Żylski W. and Gierlak P. (2010): Modelling of movement of selected manipulator (in Polish). – Acta Mechanica at Automatica, vol.4, No.1, pp.112-119.
- [14] Szuster M. (2012): Generation and Realization of Wheeled Mobile Robot Trajectory Using Neural Dynamic Programming (in Polish). – PhD Thesis, Rzeszow University of Technology.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-6266e2ae-c473-4ec7-a0f2-c6887377880d