Towards robust predictive fault-tolerant control for a battery assembly system

• Autorzy: Seybold L. , Witczak M. , Majdzik P. , Stetter R.

Identyfikatory

DOI

10.1515/amcs-2015-0061

• Języki publikacji: EN

Abstrakty

EN

The paper deals with the modeling and fault-tolerant control of a real battery assembly system which is under implementation at the RAFI GmbH company (one of the leading electronic manufacturing service providers in Germany). To model and control the battery assembly system, a unified max-plus algebra and model predictive control framework is introduced. Subsequently, the control strategy is enhanced with fault-tolerance features that increase the overall performance of the production system being considered. In particular, it enables tolerating (up to some degree) mobile robot, processing and transportation faults. The paper discusses also robustness issues, which are inevitable in real production systems. As a result, a novel robust predictive fault-tolerant strategy is developed that is applied to the battery assembly system. The last part of the paper shows illustrative examples, which clearly exhibit the performance of the proposed approach.

Słowa kluczowe

EN

max-plus algebra; interval analysis; battery assembly; model predictive control; fault tolerant control

PL

analiza interwałowa; sterowanie predykcyjne; sterowanie tolerujące uszkodzenia

• Wydawca: Oficyna Wydawnicza Uniwersytetu Zielonogórskiego
• Czasopismo: International Journal of Applied Mathematics and Computer Science
• Rocznik: 2015
• Tom: Vol. 25, no. 4
• Strony: 849--862
• Opis fizyczny: Bibliogr. 24 poz., rys., tab., wykr.

Twórcy

autor

Seybold L.

• Department of Research & Development,RAFI GmbH Co. KG, Ravensburger Straße, 128–134, D-88276 Berg/Ravensburg, Germany

autor

Witczak M.

• Institute of Control and Computation Engineering, University of Zielona Góra, ul. prof. Z. Szafrana 2, 65-516 Zielona Góra, Poland

autor

Majdzik P.

• Institute of Control and Computation Engineering, University of Zielona Góra, ul. prof. Z. Szafrana 2, 65-516 Zielona Góra, Poland

autor

Stetter R.

• Faculty of Mechanical Engineering, University of Applied Sciences Ravensburg–Weingarten, Building D., Doggenriedstraße, Weingarten, Germany

Bibliografia

• [1] Abrams, M., Doraswamy, N. and Mathur, A. (1992). Chitra: Visual analysis of parallel and distributed programs in the time, event, and frequency domains, IEEE Transactions on Parallel and Distributed Systems 3(6): 672–685.
• [2] Baccelli, F., Cohen, G., Olsder, G.J. and Quadrat, J.-P. (1992). Synchronization and Linearity: An Algebra for Discrete Event Systems, John Wiley & Sons Ltd., Chichester.
• [3] Blanke, M., Schröder, J., Kinnaert, M., Lunze, J. and Staroswiecki, M. (2006). Diagnosis and Fault-Tolerant Control, Springer, Berlin.
• [4] Butkovic, P. (2010). Max-linear Systems: Theory and Algorithms, Springer, London.
• [5] Camacho, E.F. and Bordons, C.A. (1997). Model Predictive Control in the Process Industry, Springer-Verlag New York, Inc., New York, NY.
• [6] Cechlárová, K. (2005). Eigenvectors of interval matrices over max-plus algebra, Discrete Applied Mathematics 150(1): 2–15.
• [7] Chan, C. (2002). The state of the art of electric and hybrid vehicles, Proceedings of the IEEE 90(2): 247–275.
• [8] Chen, W., Khan, A.Q., Abid, M. and Ding, S.X. (2011). Integrated design of observer-based fault detection for a class of uncertain non linear systems, International Journal of Applied Mathematics and Computer Science 21(3): 423–430, DOI: 10.2478/v10006-011-0031-0.
• [9] De Schutter, B. and Van Den Boom, T. (2001). Model predictive control for max-plus-linear discrete event systems, Automatica 37(7): 1049–1056.
• [10] Gunasekaran, A. (1999). Agile manufacturing: A framework for research and development, International Journal of Production Economics 62(1): 87–105.
• [11] Hillion, H.P. and Proth, J.-M. (1989). Performance evaluation of job-shop systems using timed event-graphs, IEEE Transactions on Automatic Control 34(1): 3–9.
• [12] Korbicz, J., Kościelny, J., Kowalczuk, Z. and Cholewa,W. (Eds.) (2004). Fault Diagnosis. Models, Artificial Intelligence, Applications, Springer-Verlag, Berlin.
• [13] Li, H., Zhao, Q. and Yang, Z. (2007). Reliability modeling of fault tolerant control systems, International Journal of Applied Mathematics and Computer Science 17(4): 491–504, DOI: 10.2478/v10006-007-0041-0.
• [14] Mrugalski, M. (2013). An unscented Kalman filter in designing dynamic GMDH neural networks for robust fault detection, International Journal of Applied Mathematics and Computer Science 23(1): 157–169, DOI: 10.2478/amcs-2013-0013.
• [15] Nair, N.-K.C. and Garimella, N. (2010). Battery energy storage systems: Assessment for small-scale renewable energy integration, Energy and Buildings 42(11): 2124–2130.
• [16] Polak, M.,Majdzik, P., Banaszak, Z. and Wójcik, R. (2004). The performance evaluation tool for automated prototyping of concurrent cyclic processes, Fundamenta Informaticae 60(1): 269–289.
• [17] Prodan, I., Olaru, S., Stoica, C. and Niculescu, S.-I. (2013). Predictive control for trajectory tracking and decentralized navigation of multi-agent formations, International Journal of Applied Mathematics and Computer Science 23(1): 91–102, DOI: 10.2478/amcs-2013-0008.
• [18] Rossiter, J. (2013). Model-based Predictive Control: A Practical Approach, CRC Press, Boca Raton, FL.
• [19] Sahner, R., Trivedi, K. and Puliafito, A. (2012). Performance and Reliability Analysis of Computer Systems: An Example-based Approach using the SHARPE Software Package, Springer Publishing Company, Inc., New York, NY.
• [20] Vincent, C. (1999). Lithium batteries, IEE Review 45(2): 65–68.
• [21] Witczak, M. (2007). Modelling and Estimation Strategies for Fault Diagnosis of Non-linear Systems, Springer-Verlag, Berlin.
• [22] Witczak, M. (2014). Fault Diagnosis and Fault-tolerant Control Strategies for Non-linear Systems, Lecture Notes in Electrical Engineering, Vol. 266, Springer International Publishing, Heidelberg.
• [23] Yan, F., Dridi, M. and El Moudni, A. (2013). An autonomous vehicle sequencing problem at intersections: A genetic algorithm approach, International Journal of Applied Mathematics and Computer Science 23(1): 183–200, DOI: 10.2478/amcs-2013-0015.
• [24] Zhang, Y. and Jiang, J. (2008). Bibliographical review on reconfigurable fault-tolerant control systems, Annual Reviews in Control 32(2): 229–252.