References
- Babuška, R. (1998). Fuzzy Modeling for Control, Kluwer Academic Publishers, Boston, MA.
- Babuˇska, R. (2000). Fuzzy Modelling and IdentificationToolbox, Version 3.1, Control Engineering Laboratory, Faculty of Information Technology and Systems, Delft University of Technology, Delft, http://lcewww.et.tudelft.nl/˜babuska.
- Bonf`e, M., Castaldi, P., Mimmo, N. and Simani, S. (2011). Active fault tolerant control of nonlinear systems: The cart-pole example, International Journal of Applied Mathematicsand Computer Science 21(3): 441-455, DOI: 10.2478/v10006-011-0033-y.
- Bosch, R. (2006). Diesel-Engine Management, 4 Edn., Wiley, Weinheim.
- Chen, J. and Patton, R.J. (1999). Robust Model-BasedFault Diagnosis for Dynamic Systems, Kluwer Academic Publishers, Boston, MA.
- Ding, S.X. (2008). Model-based Fault Diagnosis Techniques:Design Schemes, Algorithms, and Tools, 1st Edn., Springer, Berlin/Heidelberg.
- Fantuzzi, C. and Rovatti, R. (1996). On the approximation capabilities of the homogeneous Takagi-Sugeno model, Proceedings of the 5th IEEE International Conference onFuzzy Systems, New Orleans, LA, USA, pp. 1067-1072.
- Fantuzzi, C., Simani, S., Beghelli, S. and Rovatti, R. (2002). Identification of piecewise affine models in noisy environment, International Journal of Control75(18): 1472-1485.
- Isermann, R. (2005). Fault-Diagnosis Systems: An Introductionfrom Fault Detection to Fault Tolerance, 1st Edn., Springer-Verlag, Weinheim.
- Jain, T., Yam`e, J.J. and Sauter, D. (2012). Model-free reconfiguration mechanism for fault tolerance, InternationalJournal of Applied Mathematics and Computer Science22(1): 125-137, DOI: 10.2478/v10006-012-0009-6.
- Korbicz, J., Koscielny, J. M., Kowalczuk, Z. and Cholewa, W. (Eds.) (2004). Fault Diagnosis: Models, Artificial Intelligence,Applications, Springer-Verlag, London.
- Ljung, L. (1997). System Identification Toolbox for Use withMATLAB R® User’s Guide, The MathWorks, Inc., Natick, MA.
- Ljung, L. (1999). System Identification: Theory for the User, 2nd Edn., Prentice Hall, Englewood Cliffs, NJ.
- Marusak, P.M. and Tatjewski, P. (2008). Actuator fault tolerance in control systems with predictive constrained set-point optimizers, International Journal of AppliedMathematics and Computer Science 18(4): 539-551, DOI: 10.2478/v10006-008-0047-2.
- Pulkrabek, W.W. (2003). Engineering Fundamentals of theInternal Combustion Engine, 2nd Edn., Prentice Hall, Richmond, TX.
- Rovatti, R. (1996). Takagi-Sugeno models as approximators in Sobolev norms: The SISO case, 5th IEEE InternationalConference on Fuzzy Systems, New Orleans LA, USA, Vol. 2, pp. 1060-1066.
- Rovatti, R., Fantuzzi, C. and Simani, S. (2000). High-speed DSP-based implementation of piecewise-affine and piecewise-quadratic fuzzy systems, Signal ProcessingJournal 80(6): 951-963.
- Simani, S. (2007). Fault diagnosis of a simulated industrial gas turbine via identification approach, International Journalof Adaptive Control and Signal Processing 21(4): 326-353, DOI: 10.1002/acs.924.
- Simani, S., Fantuzzi, C. and Beghelli, S. (2000). Diagnosis techniques for sensor faults of industrial processes, IEEE Transactions on Control Systems Technology8(5): 848-855.
- Simani, S., Fantuzzi, C. and Patton, R.J. (2003). ModelbasedFault Diagnosis in Dynamic Systems Using IdentificationTechniques, Advances in Industrial Control, Vol. 1, Springer-Verlag, London.
- Simani, S., Fantuzzi, C., Rovatti, R. and Beghelli, S. (1999). Parameter identification for piecewise linear fuzzy models in noisy environment, International Journal of ApproximateReasoning 1(22): 149-167.
- Stamatis, D.H. (2003). Failure Mode and Effect Analysis: FMEAfrom Theory to Execution, 2nd Edn., ASQ Quality Press, Milwaukee, WI.
- Svard, C. and Nyberg, M. (2010a). Residual generators for fault diagnosis using computation sequences with mixed causality applied to automotive systems, IEEETransactions on Systems, Man and Cybernetics, PartA: Systems and Humans 40(6): 1310-1328, DOI: 10.1109/TSMCA.2010.2049993.
- Svard, C. and Nyberg, M. (2010b). Residual generators for fault diagnosis using computation sequences with mixed causality applied to automotive systems, IEEETransactions on Systems, Man and Cybernetics, PartA: Systems and Humans 40(6): 1310-1328, DOI: 10.1109/TSMCA.2010.2049993.
- Takagi, T. and Sugeno, M. (1985). Fuzzy identification of systems and its application to modeling and control, IEEE Transaction on System, Man and Cybernetics SMC-15(1): 116-132.
- Van Huffel, S. and Lemmerling, P. (Eds.) (2002). Total LeastSquares and Errors-in-Variables Modeling: Analysis, Algorithmsand Applications, 1st Edn., Springer-Verlag, London.
- Xu, D., Jiang, B. and Shi, P. (2012). Nonlinear actuator fault estimation observer: An inverse system approach via a T-S fuzzy model, International Journal of Applied Mathematicsand Computer Science 22(1): 183-196, DOI: 10.2478/v10006-012-0014-9.