Abstract
This work presents a general framework taking into account system and components reliability in a Model Predictive Control (MPC) algorithm. The objective is to deal with a closed-loop system combining a deterministic part related to the system dynamics and a stochastic part related to the system reliability from an availability point of view. The main contribution of this work consists in integrating the reliability assessment computed on-line using a Dynamic Bayesian Network (DBN) through the weights of the multiobjective cost function of the MPC algorithm. A comparison between a method based on the components reliability (local approach) and a method focused on the system reliability sensitivity analysis (global approach) is considered. The effectiveness and benefits of the proposed control framework are presented through a Drinking Water Network (DWN) simulation.
This work has been funded by the Spanish Ministry of Economy and Competitiveness through the CICYT project SHERECS (ref. DPI2011-26243), and by the European Commission through contract EFFINET (ref. FP7-ICT2011-8-318556).
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Ben, A., Muller, A., Weber, P.: Dynamic Bayesian networks in system reliability analysis. In: Proceedings of the 6th IFAC Symposium on Fault Detection. Supervision and Safety of Technical Processes, Beijing, China, pp. 481–486 (2006)
Bicking, F., Weber, P., Theilliol, D.: Reliability importance measures for fault tolerant control allocation. In: Proceedings of the 2nd International Conference on Control and Fault-tolerant Systems, Nice, France, pp. 104–109 (2013)
Bicking, F., Weber, P., Theilliol, D., Aubrun, C.: Control allocation using reliability measures for over-actuated system. In: Intelligent Systems in Technical and Medical Diagnostics, vol. 230, pp. 487–497. Springer (2014)
Birnbaum, Z.W.: On the importance of different components in a multicomponent system. In: Krishnaiah, P.R. (ed.) Multivariate Analysis, vol. 2, pp. 581–592. Academic Press, New York (1969)
Bobio, A., Portinale, L., Minichino, M., Ciancarmela, E.: Improving the analysis of dependable systems by mapping fault trees into Bayesian networks. Reliab. Eng. Syst. Saf. 17(3), 249–260 (2001)
Cox, D.R.: Regression models and life-tables. J. R. Stat. Soc. Ser. B (Methodological) 34(2), 187–220 (1972)
Finkelstein, M.S.: A note on some aging properties of the accelerated life model. Reliab. Eng. Syst. Saf. 71(1), 109–112 (2001)
Fussell, J.: How to hand-calculate system reliability and safety characteristics. IEEE Trans. Reliab. R-24(3), 169–174 (1975)
Gertsbakh, I.B.: Reliability Theory: With Applications to Preventive Maintenance. Springer, Berlin (2000)
Grosso, J.M., Ocampo-Martínez, C., Puig, V.: A service reliability model predictive control with dynamic safety stocks and actuators health monitoring for drinking water networks. In: Proceedings of the 51st IEEE Conference on Decision and Control, Hawaii, USA, pp. 4568–4573 (2012)
Jensen, F.: An Introduction to Bayesian Networks. Editions UCL Press, London (1996)
Jiang, R., Jardine, A.: Health state evaluation of an item: a general framework and graphical representation. Reliab. Eng. Syst. Saf. 93(1), 89–99 (2008)
Khelassi, A., Theilliol, D., Weber, P.: Reconfigurability analysis for reliable fault-tolerant control design. Int. J. Appl. Math. Comput. Sci. 21(3) (2011)
Khelassi, A., Theilliol, D., Weber, P., Ponsart, J.C.: Fault-tolerant control design with respect to actuator health degradation: an LMI approach. In: Proceedings of the IEEE International Conference on Control Applications, Denver, USA, pp. 983–988 (2011)
Lawless, J., Crowder, M.: Covariates and random effects in a gamma process model with application to degradation and failure. Lifetime Data Anal. 10(3), 213–227 (2004)
Levitin, G., Podofillini, L., Zio, E.: Generalised importance measures for multi-state elements based on performance level restrictions. Reliab. Eng. Syst. Saf. 82(3), 287–298 (2003)
Lu, C.J., Meeker, W.Q.: Using degradation measures to estimate a time-to-failure distribution. Technometrics 35(2), 161–174 (1993)
Maciejowski, J.M.: Predictive Control: With Constraints. Prentice Hall, Harlow (2002)
Murphy, K.P.: The Bayes net toolbox for Matlab. Comput. Sci. Stat. 33, 2001 (2001)
van Noortwijk, J.M.: A survey of the application of gamma processes in maintenance. Reliab. Eng. Syst. Saf. 94(1), 2–21 (2009)
Ocampo-Martínez, C., Puig, V., Cembrano, G., Quevedo, J.: Application of predictive control strategies to the management of complex networks in the urban water cycle. IEEE Control Syst. Mag. 33(1), 15–41 (2013)
Osaki, S., Nakagawa, T.: Bibliography for reliability and availability of stochastic systems. IEEE Trans. Reliab. R-25(4), 284–287 (1976)
Pereira, E., Galvao, R., Yoneyama, T.: Model predictive control using prognosis and health monitoring of actuators. In: Proceedings of the IEEE International Symposium on Industrial Electronics, Bari, Italy, pp. 237–243 (2010)
Salazar, J.C., Nejjari, F., Sarrate, R.: Reliable Control of a Twin Rotor MIMO System using Actuator Health Monitoring. In: Proceedings of the 22nd Mediterranean Conference on Control and Automation. pp. 481–486. Palermo, Italy (2014)
Torres-Toledano, J., Sucar, L.: Bayesian networks for reliability analysis of complex systems. In: Coelho, H. (ed.) Progress in Artificial Intelligence, pp. 195–206. Springer, Berlin (1998)
Weber, P., Jouffe, L.: Reliability modelling with dynamic Bayesian networks. IN: Proceedings of the 5th IFAC Symposium on Fault Detection. Supervision and Safety for Technical Processes, Washington D.C, USA, pp. 57–62 (2003)
Weber, P., Simon, C., Theilliol, D., Puig, V.: Fault-tolerant control design for over-actuated system conditioned by reliability: a drinking water network application. In: Proceedings of the 8th IFAC Symposium on Fault Detection. Supervision and Safety for Technical Processes, Mexico City, Mexico, pp. 558–563 (2012)
Welch, R., Thelen, T.: Dynamic reliability analysis in an operation context: the Bayesian network perspective. In: Smidts, C., Devooght, J., Labeau, P. (eds.) Dynamic Reliability: Future Directions, pp. 195–206. Maryland, USA (2000)
Wu, N.E.: Reliability of fault tolerant control systems: part I. In: Proceedings of the 40th IEEE Conference on Decision and Control, Orlando, USA, vol. 2, pp. 1460–1465 (2001)
Wu, N.E., Wang, X., Sampath, M., Kott, G.: An operational approach to budget-constrained reliability allocation. In: Proceedings of the 15th IFAC World Congress, Barcelona, Spain, pp. 113–118 (2002)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Salazar, J.C., Weber, P., Nejjari, F., Theilliol, D., Sarrate, R. (2016). MPC Framework for System Reliability Optimization. In: Kowalczuk, Z. (eds) Advanced and Intelligent Computations in Diagnosis and Control. Advances in Intelligent Systems and Computing, vol 386. Springer, Cham. https://doi.org/10.1007/978-3-319-23180-8_12
Download citation
DOI: https://doi.org/10.1007/978-3-319-23180-8_12
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-23179-2
Online ISBN: 978-3-319-23180-8
eBook Packages: EngineeringEngineering (R0)