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

Feng Xu; Vicenç Puig; Carlos Ocampo-Martinez; Sorin Olaru; Silviu-Iulian Niculescu

International Journal of Applied Mathematics and Computer Science (2017)

  • Volume: 27, Issue: 1, page 43-61
  • ISSN: 1641-876X

Abstract

top
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.

How to cite

top

Feng Xu, et al. "Robust MPC for actuator-fault tolerance using set-based passive fault detection and active fault isolation." International Journal of Applied Mathematics and Computer Science 27.1 (2017): 43-61. <http://eudml.org/doc/288093>.

@article{FengXu2017,
abstract = {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.},
author = {Feng Xu, Vicenç Puig, Carlos Ocampo-Martinez, Sorin Olaru, Silviu-Iulian Niculescu},
journal = {International Journal of Applied Mathematics and Computer Science},
keywords = {fault detection; fault isolation; set-theoretic method; fault-tolerant control; model predictive control},
language = {eng},
number = {1},
pages = {43-61},
title = {Robust MPC for actuator-fault tolerance using set-based passive fault detection and active fault isolation},
url = {http://eudml.org/doc/288093},
volume = {27},
year = {2017},
}

TY - JOUR
AU - Feng Xu
AU - Vicenç Puig
AU - Carlos Ocampo-Martinez
AU - Sorin Olaru
AU - Silviu-Iulian Niculescu
TI - Robust MPC for actuator-fault tolerance using set-based passive fault detection and active fault isolation
JO - International Journal of Applied Mathematics and Computer Science
PY - 2017
VL - 27
IS - 1
SP - 43
EP - 61
AB - 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.
LA - eng
KW - fault detection; fault isolation; set-theoretic method; fault-tolerant control; model predictive control
UR - http://eudml.org/doc/288093
ER -

References

top
  1. Alamo, T., Bravo, J. and Camacho, E. (2005). Guaranteed state estimation by zonotopes, Automatica 41(6): 1035-1043. Zbl1091.93038
  2. Blanke, M., Kinnaert, M., Lunze, J. and Staroswiecki, M. (2006). Diagnosis and Fault-Tolerant Control, Springer-Verlag, Berlin. Zbl1126.93004
  3. Borrelli, F., Bemporad, A. and Morari, M. (2013). Predictive Control for Linear and Hybrid Systems, Model Predictive Control Lab, UC, Berkeley, CA. Zbl06706347
  4. 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. 
  5. 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. 
  6. 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. 
  7. Jiang, B., Staroswiecki, M. and Cocquempot, V. (2006). Fault accommodation for nonlinear dynamic systems, IEEE Transactions on Automatic Control 51(9): 1578-1583. 
  8. 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. Zbl1140.93428
  9. 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. Zbl0923.93005
  10. 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. 
  11. 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. 
  12. 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. Zbl1116.93032
  13. 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. Zbl1207.94093
  14. 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. Zbl1205.93144
  15. 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. Zbl1348.93096
  16. 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. 
  17. 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. 
  18. Steffen, T. (2005). Control Reconfiguration of Dynamical Systems, Springer, Berlin. Zbl1137.93041
  19. 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. Zbl1157.93524
  20. 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. Zbl1273.93105
  21. 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. 
  22. 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. Zbl1322.93044
  23. 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. 
  24. 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. Zbl1273.93059

NotesEmbed ?

top

You must be logged in to post comments.

To embed these notes on your page include the following JavaScript code on your page where you want the notes to appear.

Only the controls for the widget will be shown in your chosen language. Notes will be shown in their authored language.

Tells the widget how many notes to show per page. You can cycle through additional notes using the next and previous controls.

    
                

                
Note: Best practice suggests putting the JavaScript code just before the closing </body> tag.