Abstract
Predictive control is a promising strategy for the mitigation of faults that result in more stringent operational constraints on the inputs and outputs of a system. In this context, the present work proposes a predictive control approach for accommodation of faults associated with the loss of actuator effectiveness. More specifically, it is assumed that the actuator is subject to degradation effects with progress rate proportional to the control effort. The loss of effectiveness occurs when the degradation reaches an intermediate threshold between the nominal operating condition and the total failure of the actuator. The resulting predictive control law involves the solution of a mixed-integer programming problem to be solved at each sampling instant. By imposing a suitable terminal constraint, convergence to equilibrium and recursive feasibility of the input and state constraints are ensured, provided that the optimization problem is initially feasible. Simulation results are presented for illustration.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Almeida, F. A., & Leissling, D. (2010). Fault-tolerant model predictive control with flight-test results. Journal of Guidance, Control, and Dynamics, 33(2), 363–375.
Barbosa, H. S., Galvão, R. K. H., & Yoneyama, T. (2012). Model predictive control of linear systems subject to actuator degradation. Control and Intelligent Systems, 40(4), 212–219.
Bemporad, A., & Morari, M. (1999). Control of systems integrating logic, dynamics, and constraints. Automatica, 35(3), 407–427.
Bizarria, C. O., & Yoneyama, T. (2009). Prognostics and health monitoring for an electro-hydraulic flight control actuator. In Proceedings of IEEE aerospace conference, Big Sky, USA.
Brown, D. W., Georgoulas, G., Bole, B., Pei, H. L., Orchard, M., Tang, L., Saha, B., Saxena, A., Goebel, K., & Vachtsevanos, G. (2009). Prognostics enhanced reconfigurable control of electro-mechanical actuators. In Proceedings of annual conference of the Prognostics and Health Management Society, San Diego, USA.
Franklin, G. F., Powell, J. D., & Workman, M. L. (1998). Digital control of dynamic systems (3rd ed.). Menlo Park: Addison-Wesley.
Jiang, J., & Zhang, Y. (2002). Graceful performance degradation in active fault-tolerant control systems. In Proceedings of 15th IFAC World Congress, Barcelona, Spain.
Johansen, T. A. (2015). Toward dependable embedded model predictive control. IEEE Systems Journal. doi:10.1109/JSYST.2014.2368129
Kwon, W. H., & Han, S. (2005). Receding horizon control. London: Springer.
Langeron, Y., Grall, A., & Barros, A. (2013). Actuator health prognosis for designing LQR control in feedback systems. Chemical Engineering Transactions, 33, 979–984.
Li, D., Chen, T., Marquez, H. J., & Gooden, R. K. (2006). Life extending control of boiler–turbine systems via model predictive methods. Control Engineering Practice, 14(4), 319–326.
Maciejowski, J. M. (2002). Predictive control with constraints. Harlow: Prentice-Hall.
Maciejowski, J. M., & Jones, C. N. (2003). MPC fault-tolerant flight control case study: Flight 1862. In Proceedings of IFAC symposium SAFEPROCESS, Washington, USA (pp. 119–124).
Mahulkar, V., Adams, D. E., & Derriso, M. (2009). Minimization of degradation through prognosis based control for a damaged aircraft actuator. In Proceedings of ASME dynamic systems and control conference, Hollywood, USA (pp. 669–676).
Pawlowski, A., Cervin, A., Guzmán, J. L., & Berenguel, M. (2014). Generalized predictive control with actuator deadband for event-based approaches. IEEE Transactions on Industrial Informatics, 10(1), 523–537.
Pereira, E. B., Galvão, R. K. H., & Yoneyama, T. (2010). Model predictive control using prognosis and health monitoring of actuators. In Proceedings of IEEE international symposium on industrial electronics, Bari, Italy (pp. 237–243).
Rao, V. G., & Bernstein, D. S. (2001). Naive control of the double integrator. IEEE Control Systems Magazine, 21(5), 86–97.
Rodrigues, L. R., Gomes, J. P. P., Ferri, F. A. S., Medeiros, I. P., Galvão, R. K. H., & Nascimento Júnior, C. L. (2015). Use of PHM information and system architecture for optimized aircraft maintenance planning. IEEE Systems Journal. doi:10.1109/jsyst.2014.2343752
Torrisi, F. D., & Bemporad, A. (2004). HYSDEL—A tool for generating computational hybrid models for analysis and synthesis problems. IEEE Transactions on Control Systems Technology, 12(2), 235–249.
Vachtsevanos, G., Lewis, F. L., Roemer, M., & Hess, A. (2005). Intelligent fault diagnosis and prognosis for engineering systems. New York: Wiley.
Vieira, J. P., Yoneyama, T., & Galvão, R. K. H. (2012). Reconfigurable predictive control for systems with actuator degradation: A hybrid system approach. In Proceedings of XIX Congresso Brasileiro de Automática, Campina Grande, PB, Brazil (pp. 3808–3815) (in Portuguese).
Zhang, J., Huang, X., & Cai, W. (2009). Research on prognostic and health monitoring system for large complex equipment. In Proceedings of IITA international conference on control, automation and systems engineering, Zhangjiajie, China.
Acknowledgments
Part of this work was carried out during the first author’s MSc program, which was funded by a scholarship from CAPES (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior). The authors also acknowledge the support from Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq—Research Fellowships), CAPES (PhD scholarship) and Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP—Grant 2011/17610-0).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Vieira, J.P., Galvão, R.K.H. & Yoneyama, T. Predictive Control for Systems with Loss of Actuator Effectiveness Resulting from Degradation Effects. J Control Autom Electr Syst 26, 589–598 (2015). https://doi.org/10.1007/s40313-015-0201-7
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s40313-015-0201-7