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2015 | 25 | 1 | 133-148
Tytuł artykułu

Fault tolerant control using Gaussian processes and model predictive control

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Essential ingredients for fault-tolerant control are the ability to represent system behaviour following the occurrence of a fault, and the ability to exploit this representation for deciding control actions. Gaussian processes seem to be very promising candidates for the first of these, and model predictive control has a proven capability for the second. We therefore propose to use the two together to obtain fault-tolerant control functionality. Our proposal is illustrated by several reasonably realistic examples drawn from flight control.
Rocznik
Tom
25
Numer
1
Strony
133-148
Opis fizyczny
Daty
wydano
2015
otrzymano
2014-01-31
poprawiono
2014-06-10
Twórcy
autor
  • Department of Engineering, University of Cambridge, Trumpington Street, Cambridge, CB2 1PZ, UK
  • Department of Engineering, University of Cambridge, Trumpington Street, Cambridge, CB2 1PZ, UK
Bibliografia
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  • Anon (2015). Federal motor vehicle safety standards, Standard no. 135: Light vehicle brake systems, Technical report, National Highway Traffic Safety Administration, Washington, DC, http://www.access.gpo.gov/nara/cfr/waisidx_08/49cfr571_08.html.
  • Åström, K.J. (1970). Introduction to Stochastic Control Theory, Academic Press, New York, NY.
  • Deisenroth, M. (2010). Efficient Reinforcement Learning Using Gaussian Processes, KIT Scientific Publishing, Karlsruhe.
  • Deisenroth, M. and Rasmussen, C. (2011). PILCO: A model based and data-efficient approach to policy search, Proceedings of the 28th International Conference on Machine Learning, Bellevue, WA, pp. 465-472.
  • Edwards, C., Lombaerts, T. and Smaili, H. (2010). Fault Tolerant Flight Control, Lecture Notes in Control and Information Sciences, Vol. 399, Springer-Verlag, Berlin/Heidelberg.
  • Hall, J. (2013). Machine Learning for Control: Incorporating Prior Knowledge, Ph.D. thesis, University of Cambridge, Cambridge.
  • Hall, J., Rasmussen, C. and Maciejowski, J. (2012). Modelling and control of nonlinear systems using Gaussian processes with partial model information, Proceedings of the IEEE 51st Annual Conference on Decision and Control, Maui, HI, USA, pp. 5266-5271.
  • Hartley, E., Jerez, J., Suardi, A., Maciejowski, J., Kerrigan, E. and Constantinides, G. (2012). Predictive control of a Boeing 747 aircraft using an FPGA, Proceedings of the IFAC NMPC'12 Conference, Noordwijkerhout, The Netherlands, pp. 80-85.
  • Hartley, E.N., Jerez, J.L., Suardi, A., Maciejowski, J.M., Kerrigan, E.C. and Constantinides, G.A. (2014). Predictive control using an FPGA with application to aircraft control, IEEE Transactions on Control Systems Technology 22(3): 1006-1017.
  • Huzmezan, M. and Maciejowski, J. (1999). Reconfigurable flight control during actuator failures using predictive control, 14th IFAC World Congress, Beijing, China, pp. 301-306.
  • Joosten, D. and Maciejowski, J. (2009). Model predictive controller design for fault-tolerant flight control purposes based upon an existing output feedback controller, Proceedings of the 7th IFAC Safeprocess Symposium, Barcelona, Spain, pp. 253-258.
  • Kocijan, J., Murray-Smith, R., Rasmussen, C. and Likar, B. (2003). Predictive control with Gaussian process models, Proceedings of IEEE Region 8 EUROCON 2003: Computer as a Tool, Ljubljana, Slovenia, Vol. 1, pp. 352-356.
  • Maciejowski, J.M. (1998). The implicit daisy-chaining property of constrained predictive control, Applied Mathematics and Computer Science 8(4): 695-711.
  • Maciejowski, J. (2002). Predictive Control with Constraints, Prentice-Hall, Harlow.
  • Maciejowski, J.M. (1999). Modelling and predictive control: Enabling technologies for reconfiguration, Annual Reviews in Control 23(1): 13-23.
  • Maciejowski, J. and Jones, C. (2003). Fault-tolerant flight control case study: Flight 1862, Proceedings of the 5th IFAC Safeprocess Symposium, Washington, DC, USA, pp. 265-276.
  • Maciejowski, J. and Yang, X. (2013). Fault tolerant control using Gaussian processes and model predictive control, Proceedings of the 2nd International Conference on Control and Fault-Tolerant Systems, Nice, France, pp. 1-12.
  • Rasmussen, C. and Williams, C. (2006). Gaussian Processes for Machine Learning, MIT Press, Cambridge, MA. Rawlings, J. and Mayne, D. (2009). Model Predictive Control: Theory and Design, Nob Hill Publishing, Madison, WI.
  • Snelson, E. and Ghahramani, Z. (2005). Sparse Gaussian processes using pseudo-inputs, NIPS 2005, Vancouver, Canada.
  • Wächter, A. and Biegler, L.T. (2006). On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming, Mathematical Programming 106(1): 25-57.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
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