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2012 | 22 | 4 | 929-938

Tytuł artykułu

Novel fault detection criteria based on linear quadratic control performances

Treść / Zawartość

Warianty tytułu

Języki publikacji

EN

Abstrakty

EN
This paper proposes a new approach to designing a relatively simple algorithmic fault detection system that is potentially applicable in embedded diagnostic structures. The method blends the LQ control principle with checking and evaluating unavoidable degradation in the sequence of discrete-time LQ control performance index values due to faults in actuators, sensors or system dynamics. Design conditions are derived, and direct computational forms of the algorithms are given. A simulation example subject to different types of failures is used to illustrate the design process and to demonstrate the effectiveness of the method.

Rocznik

Tom

22

Numer

4

Strony

929-938

Opis fizyczny

Daty

wydano
2012
otrzymano
2011-07-07
poprawiono
2012-02-17

Twórcy

  • Department of Cybernetics and Artificial Intelligence, Faculty of Electrical Engineering and Informatics, Technical University of Košice, Letná 9/B, 042 00 Košice, Slovakia
  • Department of Cybernetics and Artificial Intelligence, Faculty of Electrical Engineering and Informatics, Technical University of Košice, Letná 9/B, 042 00 Košice, Slovakia

Bibliografia

  • Anderson, B.D.O. and Moore, J.B. (1989). Optimal Control. Linear Quadratic Methods, Prentice-Hall, Englewood Cliffs, NJ.
  • Blanke, M., Kinnaert, M., Lunze, J. and Staroswiecki, M. (2003). Diagnosis and Fault-Tolerant Control, Springer-Verlag, Berlin.
  • Brogliato, B., Lozano, R., Maschke, B. and Egeland, O. (2007). Dissipative Systems Analysis and Control. Theory and Applications, Springer-Verlag, London.
  • Bryson A.E. (2002). Applied Linear Optimal Control. Examples and Algorithms, Cambridge University Press, Cambridge.
  • Bryson A.E. and Ho, Y.C. (1975). Applied Optimal Control. Optimization, Estimation, and Control, Taylor & Francis, New York, NY.
  • Chen, J. and Patton, R.J. (1999). Robust Model-Based Fault Diagnosis for Dynamic Systems, Kluwer, Norwell, MA.
  • Chen, W., Ding, S.X., Khan, A.Q. and Abid. M. (2010). Energy based fault detection for dissipative systems, Conference on Control and Fault Tolerant Systems, SysTol 2010, Nice, France, pp. 517-521.
  • Chen, W., Khan, A.Q., Abid. M. and Ding, S.X., (2011). Integrated design of observer based fault detection for a class of uncertain nonlinear systems, International Journal of Applied Mathematics and Computer Science 21(3): 423-430, DOI: 10.2478/v10006-011-0031-0.
  • Ding, S.X. (2009). Integrated design of control structures and embedded diagnosis, 7th IFAC International Symposium on Fault Detection, Supervision and Safety of Technical Processes, SAFEPROCESS 2009, Barcelona, Spain, pp. 734-745.
  • Dorf, R.C. and Bishop, R.H. (2011). Modern Control Systems, Pearson Education, Upper Saddle River, NJ.
  • Furuta, K. and Kim, S.B. ( 1987) Pole assignment in a specified disk, IEEE Transactions on Automatic Control 32(5): 423-427.
  • Haddad, W.M. and Chellaboina, V.S. (2003). Nonlinear Dynamical Systems and Control. A Lyapunov-Based Approach, Princeton University Press, Princeton, NJ.
  • Hendricks, E., Jannerup, O. and Sørensen P.H. (2008). Linear Systems Control. Deterministic and Stochastic Methods, Springer-Verlag, Berlin.
  • Henry, D. (2010). A norm-based point of view for fault diagnosis. Application to aerospace missions, 8th European Workshop on Advanced Control and Diagnosis, Ferrara, Italy, pp. 4-16.
  • Kirk, D.E. (1970). Optimal Control Theory. An Introduction, Prentice Hall, Englewood Cliffs, NJ.
  • Kailath, T. (1980). Linear Systems, Prentice-Hall, Englewood Cliffs, NJ.
  • Khalil, H.K. (2002). Nonlinear Systems, Prentice Hall, Upper Saddle River, NJ.
  • Khelassi, A., Theilliol, D. and Weber, P. (2011). Reconfigurability analysis for reliable fault tolerant control design, International Journal of Applied Mathematics and Computer Science 21(3): 431-439, DOI: 10.2478/v10006-011-0032-z.
  • Korbicz, J., Kościelny, J. M., Kowalczuk, Z. and Cholewa, W. (Eds.) (2004). Fault Diagnosis. Models, Artificial Intelligence, Applications, Springer-Verlag, Berlin.
  • Korbicz, J. (2007). Fault diagnosis of non-linear dynamical systems using analytical and soft computing methods, Journal of Automation, Mobile Robotics & Intelligent Systems, 1(1): 7-23.
  • Krokavec, D. (2002). Convergence of action dependent dual heuristic dynamic programming algorithms in LQ control tasks, Intelligent Technologies-Theory and Application. New Trends in Intelligent Technologies, IOS Press, Amsterdam, pp. 72-80.
  • Krokavec, D. and Filasová, A. (2008). Discrete-Time Systems, Elfa, Košice, (in Slovak).
  • Krokavec, D. and Filasová, A. (2009). Control reconfiguration based on the constrained LQ control algorithms, 7th IFAC International Symposium on Fault Detection, Supervision and Safety of Technical Processes, SAFEPROCESS 2009, Barcelona, Spain, pp. 686-691.
  • Lancaster, P. and Rodman, L. (1995). Algebraic Riccati Equations, Clarendon Press, Oxford.
  • Lewis, F.L. and Syrmos, V.L. (1995) Optimal Control, John Wiley & Sons, New York, NY.
  • Naidu, D.S. (2003). Optimal Control Systems, CRC Press, Boca Raton, FL.
  • Muhafzan (2010). Use of semidefinite programming for solving the LQR problem subject to rectangular descriptor systems, International Journal of Applied Mathematics and Computer Science 20(4): 655-664, DOI: 10.2478/v10006-010-0048-9.
  • Simani, S., Fantuzzi, C. and Patton, R.J. (2003). Model-Based Fault Diagnosis in Dynamic Systems Using Identification Techniques, Springer-Verlag, London.
  • Zolghadri, A. (2000). A redundancy-based strategy for safety management in a modern civil aircraft, Control Engineering Practice 8(5): 545-554.
  • Zolghadri, A., Castang, F., Henry, D. (2006). Design of robust fault detection filters for multivariable feedback systems, International Journal of Modeling and Simulation 26(1): 17-26.

Typ dokumentu

Bibliografia

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