Abstract
The paper addresses the issue of the state estimation problem of a class of discrete-event systems. The receding-horizon approach is employed to solve above problem. The system and its variables are described within the (max,+) algebra. Thus making possible to incorporate robustness within the overall framework. The paper also shows the transformation of the interval cost function into the scalar one, and hence, making the computational procedure trackable within the quadratic programming framework. Resulting in interval estimates of the system state, which can be used for both fault diagnosis and control purposes.
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References
1. Baccelli, F., Cohen, G., Olsder, G.J., Quadrat, J.P.: Synchronization and linearity: an algebra for discrete event systems. JOURNAL-OPERATIONAL RESEARCH SOCIETY 45, 118–118 (1994)
2. Butkovic, P.: Max-linear systems: theory and algorithms. Springer (2010)
3. Cechlárová, K.: Eigenvectors of interval matrices over max–plus algebra. Discrete applied mathematics 150(1), 2–15 (2005)
4. Elbanhawi, M., Simic, M., Jazar, R.: Receding horizon lateral vehicle control for pure pursuit path tracking. Journal of Vibration and Control p. 1077546316646906 (2016)
5. Hardouin, L., Maia, C., Cottenceau, B., Mendes, R.S.: Max-plus linear observer: Application to manufacturing systems. IFAC Proceedings Volumes 43(12), 161–166 (2010)
6. Heidergott, B., Olsder, G., van der Woude, J.: Max Plus at Work: Modeling and Analysis of Synchronized Systems: A Course on Max-Plus Algebra and Its Applications. Princeton Series in Applied Mathematics, Princeton University Press (2014), https://books.google.pl/books?id=yPocBAAAQBAJ
7. Ling, K.V., Lim, K.W.: Receding horizon recursive state estimation. IEEE Transactions on Automatic Control 44(9), 1750–1753 (1999)
8. Majdzik, P., Akielaszek-Witczak, A., Seybold, L., Stetter, R., Mrugalska, B.: A fault-tolerant approach to the control of a battery assembly system. Control Engineering Practice 55, 139–148 (2016)
9. Mrugalski, M.: Advanced neural network-based computational schemes for robust fault diagnosis, ISBN: 978-3-319-01546-0. Studies in Computational Intelligence, Vol. 510, Springer-Verlag, Berlin - Heidelberg (2014)
10. Polak, M., Majdzik, P., Banaszak, Z., Wójcik, R.: The performance evaluation tool for automated prototyping of concurrent cyclic processes. Fundamenta Informaticae 60(1-4), 269–289 (2004)
11. Puig, V.: Fault diagnosis and fault tolerant control using set-membership approaches: Application to real case studies. International Journal of Applied Mathematics and Computer Science 20(4), 619–635 (2010)
12. Seybold, L., Witczak, M., Majdzik, P., Stetter, R.: Towards robust predictive fault–tolerant control for a battery assembly system. International Journal of Applied Mathematics and Computer Science 25(4), 849–862 (2015)
13. Theilliol, D., Join, C., Zhang, Y.: Actuator fault tolerant control design based on a reconfigurable reference input. International Journal of Applied Mathematics and Computer Science 18(4), 553–560 (2008)
14. Witczak, P., Luzar, M., Witczak, M., Korbicz, J.: A robust fault-tolerant model predictive control for linear parameter-varying systems. In: Proceedings of Methods and Models in Automation and Robotics - MMAR. pp. 462–467 (2014)
15. Yoon, T.W., Clarke, D.W.: Observer design in receding-horizon predictive control. International Journal of Control 61(1), 171–191 (1995)
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Majdzik, P., Stetter, R. (2017). A receding-horizon approach to state estimation of the battery assembly system. In: Mitkowski, W., Kacprzyk, J., Oprzędkiewicz, K., Skruch, P. (eds) Trends in Advanced Intelligent Control, Optimization and Automation. KKA 2017. Advances in Intelligent Systems and Computing, vol 577. Springer, Cham. https://doi.org/10.1007/978-3-319-60699-6_27
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DOI: https://doi.org/10.1007/978-3-319-60699-6_27
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