A predictive fault-tolerant control scheme for Takagi-Sugeno fuzzy systems

Abstract In this paper, an active fault-tolerant control strategy is presented. After a short introduction to the Takagi-Sugeno fuzzy systems, a novel control strategy that integrates control and fault identification taking into account a possible actuator saturation is presented. In particular, the fault identification is based on an unknown input observer and integrated with a model-predictive controller taking into account the fault identification error. Finally, the last part of the paper exhibits experimental results regarding the tunnel furnace that confirm the effectiveness of the proposed approach.

[1]  Marcin Witczak.  Modelling and Estimation Strategies for Fault Diagnosis of Non-Linear Systems: From Analytical to Soft Computing Approaches , 2007 .

[2]  Józef Korbicz,et al.  Active fault-tolerant control design for Takagi-Sugeno fuzzy systems , 2011 .

[3]  Marcin Witczak,et al.  Advances in model-based fault diagnosis with evolutionary algorithms and neural networks , 2006 .

[4]  Stephen P. Boyd,et al.  Linear Matrix Inequalities in Systems and Control Theory , 1994 .

[5]  Stephen P. Boyd,et al.  Fast Model Predictive Control Using Online Optimization , 2010, IEEE Transactions on Control Systems Technology.

[6]  Józef Korbicz,et al.  Active fault-tolerant control design for Takagi-Sugeno fuzzy system , 2009 .

[7]  Robert M. Pap,et al.  Fault Diagnosis , 1990, Bayesian Networks in Fault Diagnosis.

[8]  Michel Kinnaert,et al.  Diagnosis and Fault-Tolerant Control , 2004, IEEE Transactions on Automatic Control.

[9]  Michio Sugeno,et al.  Fuzzy identification of systems and its applications to modeling and control , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[10]  S. Żak,et al.  Observer design for systems with unknown inputs , 2005 .

[11]  Jan M. Maciejowski,et al.  Predictive control : with constraints , 2002 .

[12]  Youmin Zhang,et al.  Bibliographical review on reconfigurable fault-tolerant control systems , 2003, Annu. Rev. Control..

[13]  G. W. Irwin,et al.  LMI-based control design for discrete polytopic LPV systems , 2003, 2003 European Control Conference (ECC).

[14]  E. Yaz.  Linear Matrix Inequalities In System And Control Theory , 1998, Proceedings of the IEEE.

[15]  Kazuo Tanaka,et al.  An approach to fuzzy control of nonlinear systems: stability and design issues , 1996, IEEE Trans. Fuzzy Syst..