PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
2017 | 27 | 1 | 43-61
Tytuł artykułu

Robust MPC for actuator-fault tolerance using set-based passive fault detection and active fault isolation

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In this paper, a fault-tolerant control (FTC) scheme is proposed for actuator faults, which is built upon tube-based model predictive control (MPC) as well as set-based fault detection and isolation (FDI). In the class of MPC techniques, tubebased MPC can effectively deal with system constraints and uncertainties with relatively low computational complexity compared with other robust MPC techniques such as min-max MPC. Set-based FDI, generally considering the worst case of uncertainties, can robustly detect and isolate actuator faults. In the proposed FTC scheme, fault detection (FD) is passive by using invariant sets, while fault isolation (FI) is active by means of MPC and tubes. The active FI method proposed in this paper is implemented by making use of the constraint-handling ability of MPC to manipulate the bounds of inputs. After the system has been detected to become faulty, the input-constraint set of the MPC controller is adjusted to actively excite the system for achieving FI guarantees on-line, where an active FI-oriented input set is designed off-line. In this way, the system can be excited in order to obtain more extra system-operating information for FI than passive FI approaches. Overall, the objective of this paper is to propose an actuator MPC scheme with as little as possible of FI conservatism and computational complexity by combining tube-based MPC and set theory within the framework of MPC, respectively. Finally, a case study is used to show the effectiveness of the proposed FTC scheme.
Rocznik
Tom
27
Numer
1
Strony
43-61
Opis fizyczny
Daty
wydano
2017
otrzymano
2015-05-04
poprawiono
2015-12-28
poprawiono
2016-08-27
zaakceptowano
2016-09-20
Twórcy
autor
  • Institut de Robòtica i Informàtica Industrial (CSIC-UPC), Technical University of Catalonia (UPC), Llorens i Artigas, 4-6, 08028 Barcelona, Spain
  • Center of Intelligent Control and Telescience, Graduate School at Shenzhen, Tsinghua University, University Town, Nanshan, 518055 Shenzhen, PR China
autor
  • Institut de Robòtica i Informàtica Industrial (CSIC-UPC), Technical University of Catalonia (UPC), Llorens i Artigas, 4-6, 08028 Barcelona, Spain
  • Institut de Robòtica i Informàtica Industrial (CSIC-UPC), Technical University of Catalonia (UPC), Llorens i Artigas, 4-6, 08028 Barcelona, Spain
autor
  • Automatic Control Department, E3S (Supélec Systems Sciences), 3 rue Joliot-Curie, 91192 Gif sur Yvette, Paris, France
  • Laboratory of Signals and Systems, CNRS-Centrale Supélec, 3 rue Joliot Curie, 91192 Gif sur Yvette, Paris, France
Bibliografia
  • Alamo, T., Bravo, J. and Camacho, E. (2005). Guaranteed state estimation by zonotopes, Automatica 41(6): 1035-1043.
  • Blanke, M., Kinnaert, M., Lunze, J. and Staroswiecki, M. (2006). Diagnosis and Fault-Tolerant Control, Springer-Verlag, Berlin.
  • Borrelli, F., Bemporad, A. and Morari, M. (2013). Predictive Control for Linear and Hybrid Systems, Model Predictive Control Lab, UC, Berkeley, CA.
  • Boskovic, J. and Mehra, R. (2002). Fault accommodation using model predictive methods, Proceedings of the 2002 American Control Conference, Anchorage, AK, USA, Vol. 6, pp. 5104-5109.
  • Hanlon, P. and Maybeck, P. (2000). Multiple-model adaptive estimation using a residual correlation Kalman filter bank, IEEE Transactions on Aerospace and Electronic Systems 36(2): 393-406.
  • Jiang, B. and Chowdhury, F. (2005). Fault estimation and accommodation for linear MIMO discrete-time systems, IEEE Transactions on Control Systems Technology 13(3): 493-499.
  • Jiang, B., Staroswiecki, M. and Cocquempot, V. (2006). Fault accommodation for nonlinear dynamic systems, IEEE Transactions on Automatic Control 51(9): 1578-1583.
  • Kofman, E., Haimovich, H. and Seron, M. (2007). A systematic method to obtain ultimate bounds for perturbed systems, International Journal of Control 80(2): 167-178.
  • Kolmanovsky, I. and Gilbert, E. (1998). Theory and computation of disturbance invariant sets for discrete-time linear systems, Mathematical Problems in Engineering 4(4): 317-367.
  • Le, V., Stoica, C., Alamo, T., Camacho, E. and Dumur, D. (2013). Zonotope-based set-membership estimation for multi-output uncertain systems, Proceedings of the 2013 IEEE international Symposium on Intelligent Control (ISIC), Hyderabad, India, pp. 212-217.
  • Maciejowski, J. (1999). Fault-tolerant aspects of MPC, IEE TwoDay Workshop on Model Predictive Control: Techniques and Applications, London, UK, pp. 1/1-1/4.
  • Mayne, D., Raković, S., Findeisen, R. and Allgöwer, F. (2006). Robust output feedback model predictive control of constrained linear systems, Automatica 42(7): 1217-1222.
  • Ocampo-Martinez, C., Doná, J.D. and Seron, M. (2010). Actuator fault-tolerant control based on set separation, International Journal of Adaptive Control and Signal Processing 24(12): 1070-1090.
  • Olaru, S., Doná, J.D., Seron, M. and Stoican, F. (2010). Positive invariant sets for fault tolerant multisensor control schemes, International Journal of Control 83(12): 2622-2640.
  • Osella, E., Haimovich, H. and Seron, M. (2015). Integration of invariant-set-based FDI with varying sampling rate virtual actuator and controller, International Journal of Adaptive Control and Signal Processing 30(2): 393-411.
  • Raimondo, D., Marseglia, G., Braatz, R. and Scott, J. (2013). Fault-tolerant model predictive control with active fault isolation, Proceedings of the 2013 Conference on Control and Fault-Tolerant Systems (SysTol), Nice, France, pp. 6567-6572.
  • Reppa, V., Olaru, S. and Polycarpou, M.M. (2015). Structural detectability analysis of a distributed sensor fault diagnosis scheme for a class of nonlinear systems, IFACPapersOnLine 48(21): 1485-1490.
  • Steffen, T. (2005). Control Reconfiguration of Dynamical Systems, Springer, Berlin.
  • Sun, S., Dong, L., Li, L. and Gu, S. (2008). Fault-tolerant control for constrained linear systems based on MPC and FDI, International Journal of Information and Systems Sciences 4(4): 512-523.
  • Xu, D., Jiang, B. and Shi, P. (2012). Nonlinear actuator fault estimation observer: An inverse system approach via a T-S fuzzy model, International Journal of Applied Mathematics and Computer Science 22(1): 183-196, DOI: 10.2478/v10006-012-0014-9.
  • Xu, F., Puig, V., Ocampo-Martinez, C., Olaru, S. and Nicolescu, S. (2014). Robust MPC for actuator-fault tolerance using set-based passive fault detection and active fault isolation, Proceedings of the IEEE Conference on Decision and Control, Los Angeles, CA, USA, pp. 4959-4964.
  • Yang, X. and Maciejowski, J.M. (2015). Fault tolerant control using Gaussian processes and model predictive control, International Journal of Applied Mathematics and Computer Science 25(1): 133-148, DOI: 10.1515/amcs-2015-0010.
  • Yetendje, A., Seron, M.M. and Doná, J.A.D. (2011). Robust MPC multicontroller design for actuator fault tolerance of constrained systems, IFAC Proceedings Volumes 44(1): 4678-4683.
  • Yetendje, A., Seron, M.M. and De Doná, J.A. (2012). Robust multisensor fault tolerant model-following MPC design for constrained systems, International Journal of Applied Mathematics and Computer Science 22(1): 211-223, DOI: 10.2478/v10006-012-0016-7.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.bwnjournal-article-amcv27i1p43bwm
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.