PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

A multi-model based adaptive reconfiguration control scheme for an electro-hydraulic position servo system

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Reliability and safety of an electro-hydraulic position servo system (EHPSS) can be greatly reduced for potential sensor and actuator faults. This paper proposes a novel reconfiguration control (RC) scheme that combines multi-model and adaptive control to compensate for the adverse effects. Such a design includes several fixed models, one adaptive model, and one reinitialized adaptive model. Each of the models has its own independent controller that is based on a complete parametrization of the corresponding fault. A proper switching mechanism is set up to select the most appropriate controller to control the current plant. The system output can track the reference model asymptotically using the proposed method. Simulation results validate robustness and effectiveness of the proposed scheme. The main contribution is a reconfiguration control method that can handle component faults and maintain the acceptable performance of the EHPSS.
Rocznik
Strony
185--196
Opis fizyczny
Bibliogr. 39 poz., rys., tab., wykr.
Twórcy
autor
  • Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, 3888 Dongnanhu Road, Erdao District, Changchun 130033, China; College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, 29 Jiangjun Ave., Jiangning District, Nanjing 211100, China
autor
  • College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, 29 Jiangjun Ave., Jiangning District, Nanjing 211100, China
autor
  • College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, 29 Jiangjun Ave., Jiangning District, Nanjing 211100, China
autor
  • Electronic Engineering Department, Aviation Key Laboratory of Science and Technology on Aero Electromechanical System Integration, 33 Shuige Road, Jiangning District, Nanjing 211100, China
  • Electronic Engineering Department, Aviation Key Laboratory of Science and Technology on Aero Electromechanical System Integration, 33 Shuige Road, Jiangning District, Nanjing 211100, China
Bibliografia
  • [1] Ahmadian, N., Khosravi, A. and Sarhadi, P. (2015). A new approach to adaptive control of multi-input multi-output systems using multiple models, Journal of Dynamic Systems, Measurement, and Control 137(9): 091009.
  • [2] Calise, A.J., Lee, S. and Sharma, M. (2001). Development of a reconfigurable flight control law for tailless aircraft, Journal of Guidance, Control, and Dynamics 24(5): 896–902.
  • [3] Chen, F., Wu, Q., Tao, G. and Jiang, B. (2014). A reconfiguration control scheme for a quadrotor helicopter via combined multiple models, International Journal of Advanced Robotic Systems 11(8): 122–132.
  • [4] Ciliz, M.K. and Tuncay, M. (2005). Comparative experiments with a multiple model based adaptive controller for a SCARA type direct drive manipulator, Robotica 23(6): 721–729.
  • [5] Falconí, G.P., Angelov, J. and Holzapfel, F. (2018). Adaptive fault-tolerant position control of a hexacopter subject to an unknown motor failure, International Journal of Applied Mathematics and Computer Science 28(2): 309–321, DOI: 10.2478/amcs-2018-0022.
  • [6] Hespanha, J., Liberzon, D., Stephen Morse, A., Anderson, B.D., Brinsmead, T.S. and De Bruyne, F. (2001). Multiple model adaptive control. Part 2: Switching, International Journal of Robust and Nonlinear Control: IFAC-Affiliated Journal 11(5): 479–496.
  • [7] Jain, T., Yamé, J.-J. and Sauter, D. (2012). Model-free reconfiguration mechanism for fault tolerance, International Journal of Applied Mathematics and Computer Science 22(1): 125–137, DOI: 10.2478/v10006-012-0009-6.
  • [8] Jiang, B., Guo, Y. and Shi, P. (2010). Adaptive reconfiguration scheme for flight control systems, Proceedings of the Institution of Mechanical Engineers I: Journal of Systems and Control Engineering 224(6): 713–723.
  • [9] Li, J.L. and Yang, G.H. (2014). Development and prospect of adaptive fault-tolerant control, Control and Decision 29(11): 1921–1926.
  • [10] Liu, L., Yao, J., Ma, D. and Wang, G. (2019). Low-frequency learning-based robust adaptive control for electro-hydraulic position servo system, Acta Armamentarii 40(4): 737–743.
  • [11] Ma, J. (2003). Research on Intelligent Pump and Its Experiment System, PhD thesis, Beijing University of Aeronautics and Astronautics, Beijing.
  • [12] Manring, N.D. and Fales, R.C. (2019). Hydraulic Control Systems, John Wiley & Sons, New York.
  • [13] Mark, B., Andreas, S., Marco, M. and Rolf, I. (2010). Active fault tolerant control of an electro-hydraulic servo axis with a duplex-valve-system, IFAC Proceedings Volumes 43(18): 660–668.
  • [14] Maybeck, P.S. (1999). Multiple model adaptive algorithms for detecting and compensating sensor and actuator/surface failures in aircraft flight control systems, International Journal of Robust and Nonlinear Control 9(14): 1051–1070.
  • [15] Mejdi, S., Messaoud, A. and Ben Abdennour, R. (2020). Fault tolerant multicontrollers for nonlinear systems: A real validation on a chemical process, International Journal of Applied Mathematics and Computer Science 30(1): 61–74, DOI: 10.34768/amcs-2020-0005.
  • [16] Milic, V., Situm, Z. and Essert, M. (2010). Robust H infinity position control synthesis of an electro-hydraulic servo system, ISA Transactions 49(4): 535–542.
  • [17] Mintsa, H.A., Venugopal, R., Kenne, J.P. and Belleau, C. (2011). Feedback linearization-based position control of an electrohydraulic servo system with supply pressure uncertainty, IEEE Transactions on Control Systems Technology 20(4): 1092–1099.
  • [18] Narendra, S.K. and Balakrishnan, J. (1997). Adaptive control using multiple models, IEEE Transactions on Automatic Control 42(2): 171–187.
  • [19] Niksefat, N. and Sepehri, N. (2001). Fault tolerant control of electrohydraulic servo positioning systems, Proceedings of the 2001 American Control Conference, Arlington, USA, pp. 4472–4477.
  • [20] Niksefat, N. and Sepehri, N. (2002). A QFT fault-tolerant control for electrohydraulic positioning systems, IEEE Transactions on Control Systems Technology 10(4): 626–632.
  • [21] Pazera, M., Buciakowski, M. and Witczak., M. (2018). Robust multiple sensor fault-tolerant control for dynamic non-linear systems: Application to the aerodynamical twin-rotor system, International Journal of Applied Mathematics and Computer Science 28(2): 297–308, DOI: 10.2478/amcs-2018-0021.
  • [22] Salazar, J.C., Sanjuan, A., Nejjari, F. and Sarrate, R. (2020). Health-aware and fault-tolerant control of an octorotor UAV system based on actuator reliability, International Journal of Applied Mathematics and Computer Science 30(1): 47–59, DOI: 10.34768/amcs-2020-0004.
  • [23] Salleh, S., Rahmat, M.F., Othman, S.M. and Danapalasingam, K.A. (2015). Review on modeling and controller design of hydraulic actuator systems, International Journal on Smart Sensing & Intelligent Systems 8(1): 338–367.
  • [24] Sharifi, S., Tivay, A., Rezaei, S.M., Zareinejad, M. and Mollaei Dariani, B. (2018). Leakage fault detection in electro-hydraulic servo systems using a nonlinear representation learning approach, ISA Transactions 73: 154–164.
  • [25] Shin, D.H. and Kim, Y. (2004). Reconfigurable flight control system design using adaptive neural networks, IEEE Transactions on Control Systems Technology 12(1): 87–100.
  • [26] Si, G., Shen, Y., Wang, J., Cao, T. and Wan, M. (2020). Active disturbance rejection control of electro-hydraulic position servo system, Chinese Hydraulics & Pneumatics 12(3): 14–21.
  • [27] Sofianos, N.A. and Boutalis, Y.S. (2016). Robust adaptive multiple models based fuzzy control of nonlinear systems, Neurocomputing 173: 1733–1742.
  • [28] Sun,W., Jian, D., Yuan, Y. and Yuan, Y. (2016). Fault simulation of electro-hydraulic servo system for fault self-healing based on immune principle, 2016 9th International Symposium on Computational Intelligence and Design (ISCID), Hangzhou, China, pp. 136–139.
  • [29] Tan, C., Tao, G. and Qi, R. (2014). An adaptive control scheme using multiple reference models, International Journal of Adaptive Control and Signal Processing 28(11): 1290–1298.
  • [30] Tan, C., Yao, X.and Tao, G. and Qi, R. (2012). A multiple-model based adaptive actuator failure compensation scheme for control of near-space vehicles, IFAC Proceedings Volumes 45(20): 594–599.
  • [31] Tang, R. and Zhang, Q. (2011). Dynamic sliding mode control scheme for electro-hydraulic position servo system, Procedia Engineering 24: 28–32.
  • [32] Wang, C., Shang, Y., Jiao, Z. and Han, S. (2014). Nonlinear robust control of valve controlled electro-hydraulic position servo system, Journal of Beijing University of Aeronautics and Astronautics 40(12): 1736–1740.
  • [33] Wang, H. (2017). Research on an Adaptive Sliding Mode Control Strategy for Electro-Hydraulic Position Servo System, PhD thesis, Shanghai Jiao Tong University, Shanghai.
  • [34] Yao, J., Jiao, Z., Shang, Y. and Huang, C. (2010). Adaptive nonlinear optimal compensation control for electro-hydraulic load simulator, Chinese Journal of Aeronautics 23(6): 101–114.
  • [35] Yu, X. and Jiang, J. (2011). Hybrid fault-tolerant flight control system design against partial actuator failures, IEEE Transactions on Control Systems Technology 20(4): 871–886.
  • [36] Yu-Ying, G. and Jiang, B. (2009). Multiple model-based adaptive reconfiguration control for actuator fault, Acta Automatica Sinica 35(11): 1452–1458.
  • [37] Yuan, H.B., Na, H.C. and Kim, Y.B. (2018). System identification and robust position control for electro-hydraulic servo system using hybrid model predictive control, Journal of Vibration and Control 24(18): 4145–4159.
  • [38] Zhai, J., Fei, S. and Da, F. (2006). Intelligent control using multiple models based on on-line learning, Journal of Control Theory and Applications 4(4): 397–401.
  • [39] Zhang, Z., Yang, Z., Xiong, S., Chen, S., Liu, S. and Zhang, X. (2021). Simple adaptive control-based reconfiguration design of cabin pressure control system, Complexity 2021(3): 1–16.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-4dc8dc1d-6d42-4fed-a483-c595e3bf20cf
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.