Robust multisensor fault tolerant model-following MPC design for constrained systems

• Autorzy: Yetendje A. , Seron M. M. , De Doná J. A.
• Języki publikacji: EN

Abstrakty

EN

In this paper, a robust fault-tolerant control strategy for constrained multisensor linear systems, subject to sensor faults and in the presence of bounded state and output disturbances, is proposed. The scheme verifies that, for each sensors-estimator combination, suitable residual variables lie inside pre-computed sets and selects a more appropriate combination based on a chosen criterion. An active fault tolerant output feedback controller yields an MPC-based control law and, by means of the notion of a "tube" of trajectories, we ensure robust closed-loop exponential stability and good performance in the fault-free case and under the occurrence of abrupt sensor faults.

Słowa kluczowe

EN

fault tolerant control; constraints; robustness; invariant set

PL

sterowanie tolerujące uszkodzenia; odporność; ograniczenie

• Wydawca: Oficyna Wydawnicza Uniwersytetu Zielonogórskiego
• Czasopismo: International Journal of Applied Mathematics and Computer Science
• Rocznik: 2012
• Tom: Vol. 22, no. 1
• Strony: 211--223
• Opis fizyczny: Bibliogr. 22 poz., rys., wykr.

Twórcy

autor

Yetendje A.

autor

Seron M. M.

autor

De Doná J. A.

• Centre for Complex Dynamic Systems and Control (CDSC) School of Electrical Engineering and Computer Science University of Newcastle, Callaghan, NSW 2308, Australia,

Bibliografia

• [1] De Doná, J., Seron, M. and Yetendje, A. (2009). Multisensor fusion fault-tolerant control with diagnosis via a set separation principle, Proceedings of the 48th IEEE Conference on Decision and Control, Shanghai, China, pp. 7825-7830.
• [2] Goodwin, G., Seron, M. and De Doná, J. (2005). Constrained Control and Estimation-An Optimisation Approach, Springer-Verlag, London.
• [3] Jemaa, L. B. and Davison, E. (2003). Performance limitations in the robust servomechanism problem for discrete-time LTI systems, IEEE Transactions on Automatic Control 48(8): 1299-1311.
• [4] Kofman, E., Haimovich, H. and Seron, M. M. (2007). A systematic method to obtain ultimate bounds for perturbed systems, International Journal of Control 80(2): 167-178.
• [5] Larson, E. C., Jr, B. P. and Clark, B. R. (2002). Model-based sensor and actuator fault detection and isolation, Proceedings of the American Control Conference, Anchorage, AK, USA, Vol. 5, pp. 4215-4219.
• [6] Maciejowski, J. (1999). Fault-tolerant aspects of MPC, Proceedings of the IEEE Workshop on Model Predictive Control: Techniques and Applications, London, UK, pp. 1/1-1/4.
• [7] Maciejowski, J. (2002). Predictive Control with Constraints, Prentice-Hall, Pearson Education Limited, Harlow.
• [8] Martínez, J. J. and de Wit, C. C. (2004). Model reference control approach for safe longitudinal control, Proceedings of the 2004 American Control Conference, Boston, MA, USA, Vol. 3, pp. 2757-2762.
• [9] Mayne, D. Q., Rakovic, S. V., Findeisen, R. and Allgöwer, F. (2006). Robust output feedback model predictive control of constrained linear systems, Automatica 42(7): 1217-1222.
• [10] Mendonça, L., Vieira, S., Sousa, J. and da Costa, J. S. (2006). Fault accommodation using fuzzy predictive control, Proceedings of the IEEE International Conference on Fuzzy Systems, Vancouver, BC, pp. 1535-1542.
• [11] Mhaskar, P. (2006). Robust model predictive control design for fault-tolerant control of process systems, Industrial & Engineering Chemistry Research 45(25): 8565-8574.
• [12] Mhaskar, P., Gani, A. and Christofides, P. (2006). Fault-tolerant control of nonlinear processes: Performance-based reconfiguration and robustness, International Journal of Robust Nonlinear Control 16(3): 91-111.
• [13] Ocampo-Martinez, C. and Puig, V. (2008). Fault-tolerant control model predictive control within the hybrid systems framework: Application to sewer networks, International Journal of Adaptive Control and Signal Processing 23(8): 757-787.
• [14] Patwardhan, S., Manuja, S., Narsimhan, S. and Shah, S. (2006). From data to diagnosis and control using generalized orthonormal basis filters, Part II: Model predictive and fault tolerant control, Journal of Process and Control 16(2): 157-175.
• [15] Pranatyasto, T. N. and Qin, S. (2001). Sensor validation and process fault diagnosis for FCC units under MPC feedback, Control Engineering Practice 9(8): 877-888.
• [16] Rawlings, J. B. and Mayne, D. Q. (2009). Model Predictive Control: Theory and Design, Nob Hill Publishing, Madison, WI.
• [17] Seron, M., Zhuo, X., De Doná, J. and Martínez, J. (2008). Multisensor switching control strategy with fault tolerance guarantees, Automatica 44(1): 88-97.
• [18] Sheng-Qi, S., Dong, L., Lin, L. and Shu-Sheng, G. (2008). Fault tolerant control for constrained linear systems based on MPC and FDI, International Journal of Information and Systems Sciences 4(4): 512-523.
• [19] Sun, S. and Deng, Z. (2008). Distributed optimal fusion steady state Kalman filter for systems with coloured measurement noises, International Journal of Systems Science 36(3): 113-118.
• [20] Yetendje, A., De Doná, J. and Seron, M. (2011). Multisensor fusion fault-tolerant control, Automatica 47(7): 1461-1466.
• [21] Yetendje, A., Seron, M. and De Doná, J. (2010). Robust MPC design for fault tolerance of constrained multisensor linear systems, Conference on Control and Fault-Tolerant Systems (SysTol' 10), Nice, France, pp. 752-758.
• [22] Yetendje, A., Seron, M., De Doná, J. and Martínez, J. J. (2010). Sensor fault-tolerant control of a magnetic levitation system, International Journal of Robust and Nonlinear Control 20(18): 2108-2121.