Powiadomienia systemowe
- Sesja wygasła!
Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
The paper describes a nonlinear controller design technique applied to a servo drive in the presence of hard state constraints. The approach presented is based on nonlinear state-space transformation and adaptive backstepping. It allows us to impose hard constraints on the state variables directly and to achieve asymptotic tracking of any reference trajectory inside the constraints, despite unknown plant parameters. Two control schemes (with and without integral action) are derived, investigated and then compared. Several examples demonstrate the main features of the design procedure and prove that it may be applied in case of motion control problems in electric drive automation.
Słowa kluczowe
Rocznik
Tom
Strony
963–--971
Opis fizyczny
Bibliogr. 26 poz., rys., tab.
Twórcy
autor
- Institute of Automatic Control, Lodz University of Technology, Stefanowskiego 18/22 Lodz, Poland
autor
- Institute of Automatic Control, Lodz University of Technology, Stefanowskiego 18/22 Lodz, Poland
Bibliografia
- [1] F. Blanchini, “Set invariance in control”, Automatica 35(11) 1747–1767 (1999).
- [2] E. Pérez, C. Ariño, F.X. Blasco, and M.A. Martínez, “Maximal closed loop admissible set for linear systems with non-convex polyhedral constraints”, J. Process Control 21(4), 529–537 (2011).
- [3] E.G. Gilbert and K.T. Tan, “Linear systems with state and control constraints: the theory and application of maximal output admissible sets”, IEEE Trans. Automat. Contr. 36(9), 1008–1020 (1991).
- [4] R. Wang and J. Bao, “A differential Lyapunov-based tube MPC approach for continuous-time nonlinear processes”, J. Process Control 83, 155–163 (2019).
- [5] D.Q. Mayne, J.B. Rawlings, C.V. Rao, and P.O.M. Scokaert, “Constrained model predictive control: stability and optimality”, Automatica 36(6), 789–814 (2000).
- [6] K. Kogiso and K. Hirata, “Reference governor for constrained systems with time-varying references”, Rob. Auton Syst. 57(3), 289–295 (2009).
- [7] S. Oh-hara, Y. Urano, and F. Matsuno, “The control of constrained system with time-delay and its experimental evaluations using RC model helicopter”, in 2007 International Conference on Control, Automation and Systems, 2007, pp. 2897–2901.
- [8] J. Li and Y. Liu, “Control of nonlinear systems with full state constraints using integral Barrier Lyapunov Functionals”, in 2015 International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS), 2015, pp. 66–71.
- [9] W. Wang and S. Tong, “Adaptive fuzzy containment control of nonlinear strict-feedback systems with full state constraints”, IEEE Trans. Fuzzy Syst. 27(10), 2024–2038 (2019).
- [10] K. Sachan and R. Padhi, “Output-constrained robust adaptive control for uncertain nonlinear MIMO systems with unknown control directions”, IEEE Control Syst. Lett. 3(4), 823–828 (2019).
- [11] S. Luo and Y. Song, “Chaos analysis-based adaptive backstepping control of the microelectromechanical resonators with constrained output and uncertain time delay”, IEEE Trans. Ind. Electron. 63(10), 6217–6225 (2016).
- [12] C. Wang, Y. Wu, and J. Yu, “Barrier Lyapunov functions-based adaptive control for nonlinear pure-feedback systems with time-varying full state constraints”, Int. J. Control. Autom. Syst. 15(6), 2714–2722 (2017).
- [13] C. Wang, Y. Wu, F. Wang, and Y. Zhao, “TABLF-based adaptive control for uncertain nonlinear systems with time-varying asymmetric full-state constraints”, Int. J. Control (2019), doi: 10.1080/00207179.2019.1639825.
- [14] Z. Yin, B. Wang, C. Du, and Y. Zhang, “Barrier-Lyapunov-function-based backstepping control for PMSM servo system with full state constraints”, in 2019 22nd International Conference on Electrical Machines and Systems (ICEMS), 2019, pp. 1–5.
- [15] J. Kabziński, P. Mosiołek, and M. Jastrzębski, “Adaptive position tracking with hard constraints – barrier Lyapunov functions approach”, in Studies in Systems, Decision and Control, vol. 75, Springer Berlin Heidelberg, pp. 27–52, 2017.
- [16] Z.L. Tang, S.S. Ge, K.P. Tee, and W. He, “Robust adaptive neural tracking control for a class of perturbed uncertain nonlinear systems with state constraints”, IEEE Trans. Syst. Man, Cybern. Syst. 46(12), 1618–1629 (2016).
- [17] K.P. Tee and S.S. Ge, “Control of nonlinear systems with partial state constraints using a barrier Lyapunov function”, Int. J. Control. 84(12), 2008–2023 (2011).
- [18] J. Kabziński, “Adaptive, compensating control of wheel slip in railway vehicles”, Bull. Pol. Ac.: Tech. 63(4), 955–963 (2015).
- [19] P. Serkies, “A novel predictive fuzzy adaptive controller for a two-mass drive system”, Bull. Pol. Ac.: Tech. 66(1), 37–47 (2018).
- [20] T. Białoń, M. Pasko, A. Lewicki, and R. Niestrój, “Parameter selection of an adaptive PI state observer for an induction motor”, Bull. Pol. Ac.: Tech. 61(3), 599–603 (2013).
- [21] T. Orlowska-Kowalska and M. Dybkowski, “Performance analysis of the sensorless adaptive sliding-mode neuro-fuzzy control of the induction motor drive with MRAS-type speed estimator”, Bull. Pol. Ac.: Tech. 60(1), 61–70 (2012).
- [22] M. Krstic, K. Ioannis, and P.V. Kokotovic, Nonlinear and Adaptive Control Design, Wiley, 1995.
- [23] J. Kabziński and P. Mosiołek, Projektowanie nieliniowych układów sterowania (Nonlinear Control Design), Wydawnictwo Naukowe PWN, 2018.
- [24] H.K. Khalil, Nonlinear Systems, Prentice Hall, 2000
- [25] C. Makkar, G. Hu, W.G. Sawyer, and W.E. Dixon, “Lyapunov-Based Tracking Control in the Presence of Uncertain Nonlinear Parameterizable Friction”, IEEE Trans. Automat. Contr. 52(10), 1988–1994 (2007).
- [26] Y. Zhang, S. Li, X. Luo, and M. Shang, “A dynamic neural controller for adaptive optimal control of permanent magnet DC motors, in 2017 International Joint Conference on Neural Networks (IJCNN), 2017, pp. 839–844.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-7f23a4ae-e61a-4797-9d0b-f685adb93684