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A safe supervisory flight control scheme in the presence of constraints and anomalies

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In this paper the hybrid supervisory control architecture developed by Famularo et al. (2011) for constrained control systems is adopted with the aim to improve safety in aircraft operations when critical events like command saturations or unpredicted anomalies occur. The capabilities of a low-computational demanding predictive scheme for the supervision of non-linear dynamical systems subject to sudden switchings amongst operating conditions and time-varying constraints are exploited in the flight control systems framework. The strategy is based on command governor ideas and is tailored to jointly take into account time-varying set-points/constraints. Unpredictable anomalies in the nominal plant behaviour, whose models fall in the category of time-varying constraints, can also be tolerated by the control scheme. In order to show the effectiveness of the proposed approach, simulations both on a high altitude performance demonstrator unmanned aircraft with redundant control surfaces and the P92 general aviation aircraft are discussed.
Rocznik
Strony
39--51
Opis fizyczny
Bibliogr. 32 poz., rys., tab., wykr.
Twórcy
autor
  • Dipartimento di Informatica, Modellistica, Elettronica e Sistemistica, Università della Calabria, Via Pietro Bucci, Cubo 42-C, Rende (CS), 87036, Italy
autor
  • Dipartimento di Informatica, Modellistica, Elettronica e Sistemistica, Università della Calabria, Via Pietro Bucci, Cubo 42-C, Rende (CS), 87036, Italy
autor
  • Ingegneria Industriale e dell’Informazione, Seconda Università degli Studi di Napoli, Real Casa dell’Annunziata Via Roma, 29, Aversa (CE), 81031, Italy
  • Dipartimento di Ingegneria, delle Infrastrutture e dell’Energia Sostenibile, Università degli Studi di Reggio Calabria, Reggio Calabria, Via Graziella, loc. Feo di Vito, 89060, Italy
Bibliografia
  • [1] Angeli, D., and Mosca, E. (1999). Command governors for constrained nonlinear systems, IEEE Transactions on Automatic Control 44(4): 816–820.
  • [2] Angeli, D., Casavola, A. and Mosca, E. (2001). On feasible set-membership state estimators in constrained command governor control, Automatica 37(1): 151–156.
  • [3] Bacconi, F., Mosca, E. and Casavola, A. (2007). Hybrid constrained formation flying control of micro-satellites, IET Control Theory Applications 1(2): 513–521.
  • [4] Bemporad, A., Casavola, A. and Mosca, E. (1997). Nonlinear control of constrained linear systems via predictive reference management, IEEE Transactions on Automatic Control 42(3): 340–349.
  • [5] Bemporad, A. (1998). Reference governor for constrained nonlinear systems, IEEE Transactions on Automatic Control 43(3): 415–419.
  • [6] Blackford, L.S., Demmel, J., Dongarra, J., Duff, I., Hammarling, S., Henry, G., Heroux, M., Kaufman, L., Lumsdaine, A., Petitet, A., Pozo, R., Remington, K. and Whaley R.C. (2003). An updated set of basic linear algebra subprograms (BLAS), ACM Transactions on Mathematical Software 28(2): 135–151.
  • [7] Blanke, M., Kinnaert, M., Lunze, J. and Staroswiecki, M. (2006). Diagnosis and Fault Tolerant Control, Springer-Verlag, Berlin/Heidelberg.
  • [8] Branicky, M.S. (1998). Multiple Lyapunov functions and other analysis tools for switched and hybrid systems, IEEE Transactions on Automatic Control 43(4): 475–482.
  • [9] Chen, S.H., Tao, G., and Joshi, S.M. (2002). On matching conditions for adaptive state tracking control of systems with actuator failures, IEEE Transactions on Automatic Control 47(3): 473–478.
  • [10] Famularo, D., Franzè, G., Furfaro, A. and Mattei, M. (2011). A hybrid real-time supervisory scheme for nonlinear systems, Proceedings of the 2011 American Control Conference, ACC 2011, San Francisco CA, USA, pp. 305–310.
  • [11] Franzè, G., Furfaro, A., Mattei, M. and Scordamaglia, V. (2013). An hybrid command governor supervisory scheme for flight control systems subject to unpredictable anomalies, Proceedings of the 2nd International Conference on Control and Fault-Tolerant Systems, Nice, France, (CD-ROM).
  • [12] Gao, Z. and Antsaklis, P.K. (1991). Stability of the pseudo-inverse method for reconfigurable control systems, International Journal of Control 53(3): 717–729.
  • [13] Garone, E., Tedesco, F., and Casavola, A. (2010). A feed-forward command governor strategy for constrained linear systems, Proceedings of Nolcos 2010, Bologna, Italy.
  • [14] Gilbert, E.G., Kolmanovsky, I. and Tin Tan, K. (1995). Discrete-time reference governors and the nonlinear control of systems with state and control constraint, International Journal of Robust and Nonlinear Control 5(5): 487–504.
  • [15] Gilbert, E.G. and Kolmanovsky, I. (1999). Fast reference governors for systems with state and control constraint and disturbance inputs, International Journal of Robust and Nonlinear Control 9(15): 1117–1141.
  • [16] Guo, C. and Song, Q. (1999). Real-time control of variable air volume system based on a robust neural network assisted PI controller, IEEE Transactions on Control Systems Technology 17(3): 600–607.
  • [17] Iserman, R.. and Ballè, P. (1997). Trends in the application of model-based fault detection and diagnosis of technical processes, Control Engineering Practice 5(5): 709–719.
  • [18] Khalil, H.K. (1996). Nonlinear Systems, Prentice Hall, Upper Saddle River, NJ.
  • [19] Magree, D., Yucelen, T., and Johnson, E.N. (2012). Command governor-based adaptive control of an autonomous helicopter, Proceedings of the AIAA Conference, Minneapolis, MI, USA, pp. 1–13.
  • [20] Mattei, M., Famularo, D. and Labate, C.V. (2013). A constrained control strategy for the shape control in thermonuclear fusion tokamaks, Automatica 49(1): 169–177.
  • [21] Mhaskar, P., McFall, C., Gani, A., Christofides, P.D., and Davis, J. F. (2008). Isolation and handling of actuator faults in nonlinear systems, Automatica 44(1): 53–62.
  • [22] Micksh, T., Gambier A. and Badreddin, E. (2008). Real-time implementation of fault-tolerant control using model predictive control, Proceedings of the 17th IFAC World Congress, Seoul, Korea, pp. 11136–11141.
  • [23] Park, S.J. and Yang, J.M. (2009). Supervisory control for real-time scheduling of periodic and sporadic tasks with resource constraint, Automatica 45(11): 2597–2604.
  • [24] Patton, R.J. (1997). Real-time implementation of fault-tolerant control using model predictive control, Proceedings of the 3rd IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes, Hull, UK, pp. 1033–1055.
  • [25] Scordamaglia, V., Sollazzo A. and Mattei, M. (2012). Fixed structure flight control design of an over-actuated aircraft in the presence of actuators with different dynamic performance, Proceedings of the 7th IFAC Symposium on Robust Control Design, Aalborg, Denmark, (CD-ROM).
  • [26] Seron, M.M., De Dona, J.A., and Olaru, S. (2013). Fault tolerant control allowing sensor healthy-to-faulty and faulty-to-healthy transitions, IEEE Transactions on Automatic Control 57(7): 1657–1669.
  • [27] Staroswiecki, M. (2010). On reconfiguration-based fault tolerance, Proceedings of the 18th Mediterranean Conference on Control and Automation (MED), Marrakech, Marocco, pp. 1681–1691.
  • [28] Stevens, B.R. and Lewis, F.L. (1992). Aircraft Control and Simulation, Wiley Interscience, New York, NY.
  • [29] Steffen, T. (2005). Control Reconfiguration of Dynamical Systems, Lecture Notes in Control and Information Science, Vol. 320, Springer-Verlag, Berlin/Heidelberg.
  • [30] Tan, W. and Packard, A. (2008). Stability region analysis using polynomial and composite polynomial Lyapunov functions and sum-of-squares programming, IEEE Transactions on Automatic Control 53(2): 565–571.
  • [31] Zhang, Y. and Jiang, J. (2008). Bibliographical review on reconfigurable fault-tolerant control systems, Annual Reviews in Control 32(2): 229–252.
  • [32] Wang, Y. and Boyd, S. (2010). Fast model predictive control using online optimization, IEEE Transactions on Control Systems Technology 18(2): 267–278.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-3824a8ff-43a4-4340-9084-573b1fe8f259
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