Fault Detection in Finite Frequency Domain for Takagi-Sugeno Fuzzy Systems With Sensor Faults

This paper is concerned with the fault detection (FD) problem in finite frequency domain for continuous-time Takagi-Sugeno fuzzy systems with sensor faults. Some finite-frequency performance indices are initially introduced to measure the fault/reference input sensitivity and disturbance robustness. Based on these performance indices, an effective FD scheme is then presented such that the generated residual is designed to be sensitive to both fault and reference input for faulty cases, while robust against the reference input for fault-free case. As the additional reference input sensitivity for faulty cases is considered, it is shown that the proposed method improves the existing FD techniques and achieves a better FD performance. The theory is supported by simulation results related to the detection of sensor faults in a tunnel-diode circuit.

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

[2]  Kazuo Tanaka,et al.  Stability analysis and design of fuzzy control systems , 1992 .

[3]  Paul M. Frank,et al.  A frequency domain approach to fault detection of uncertain dynamic systems , 1993, Proceedings of 32nd IEEE Conference on Decision and Control.

[4]  Steven X. Ding,et al.  Frequency domain approach to optimally robust residual generation and evaluation for model-based fault diagnosis , 1994, Autom..

[5]  Michel Kinnaert,et al.  Residual generator for sensor and actuator fault detection and isolation: a frequency domain approach , 1995 .

[6]  P. Frank,et al.  Survey of robust residual generation and evaluation methods in observer-based fault detection systems , 1997 .

[7]  J. Doyle,et al.  Essentials of Robust Control , 1997 .

[8]  Michèle Basseville,et al.  Fault Detection and Isolation in Nonlinear Dynamic Systems: A Combined Input-Output and Local Approach , 1998, Autom..

[9]  Hugh F. Durrant-Whyte,et al.  The detection of faults in navigation systems: a frequency domain approach , 1998, Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146).

[10]  Janos Gertler,et al.  Fault detection and diagnosis in engineering systems , 1998 .

[11]  Dominique Sauter,et al.  Frequency-domain optimization for robust fault detection and isolation in dynamic systems , 1999, IEEE Trans. Autom. Control..

[12]  Hassan Hammouri,et al.  Observer-based approach to fault detection and isolation for nonlinear systems , 1999, IEEE Trans. Autom. Control..

[13]  Alberto Isidori,et al.  A Geometric Approach to Nonlinear Fault Detection and Isolation , 2000 .

[14]  Torsten Jeinsch,et al.  A unified approach to the optimization of fault detection systems , 2000 .

[15]  Truong Q. Nguyen,et al.  Robust and reduced-order filtering: new LMI-based characterizations and methods , 2001, IEEE Trans. Signal Process..

[16]  Y. Soh,et al.  Reliable H 8 controller design for linear systems , 2001 .

[17]  Jianliang Wang,et al.  Reliable Hinfinity controller design for linear systems , 2001, Autom..

[18]  Hassan Hammouri,et al.  A geometric approach to fault detection and isolation for bilinear systems , 2001, IEEE Trans. Autom. Control..

[19]  S. Nguang,et al.  H/sub /spl infin// filtering for fuzzy dynamical systems with D stability constraints , 2003 .

[20]  S. Hara,et al.  Generalization of Kalman-Yakubovic-Popov lemma for restricted frequency inequalities , 2003, Proceedings of the 2003 American Control Conference, 2003..

[21]  S. Nguang,et al.  Hinfinity fuzzy control design for nonlinear singularly perturbed systems with pole placement constraints: an LMI approach. , 2004, IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society.

[22]  Alexander L. Fradkov,et al.  Restricted frequency inequality is equivalent to restricted dissipativity , 2004, 2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601).

[23]  Alessandro Casavola,et al.  A robust deconvolution scheme for fault detection and isolation of uncertain linear systems: an LMI approach , 2005, Autom..

[24]  Alessandro Casavola,et al.  Robust fault detection of uncertain linear systems via quasi-LMIs , 2005 .

[25]  D. Henry,et al.  Design and analysis of robust residual generators for systems under feedback control , 2005, Autom..

[26]  Guang-Hong Yang,et al.  Adaptive Fault-Tolerant Tracking Control Against Actuator Faults With Application to Flight Control , 2006, IEEE Transactions on Control Systems Technology.

[27]  Peng Shi,et al.  Fault Detection for Uncertain Fuzzy Systems: An LMI Approach , 2007, IEEE Transactions on Fuzzy Systems.

[28]  Guanghong Yang,et al.  H ∞ Filtering for Fuzzy Singularly Perturbed Systems , 2008 .

[29]  Guang-Hong Yang,et al.  $H_{\infty}$ Filtering for Fuzzy Singularly Perturbed Systems , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[30]  Heng Wang,et al.  A finite frequency domain approach to fault detection for linear discrete-time systems , 2008, Int. J. Control.

[31]  Guanghong Yang,et al.  Fault Detection Observer Design in Low Frequency Domain for Linear Time-delay Systems: Fault Detection Observer Design in Low Frequency Domain for Linear Time-delay Systems , 2009 .

[32]  Guanghong Yang,et al.  Fault Detection Observer Design in Low Frequency Domain for Linear Time-delay Systems , 2009 .

[33]  Daniel W. C. Ho,et al.  Fuzzy Filter Design for ItÔ Stochastic Systems With Application to Sensor Fault Detection , 2009, IEEE Transactions on Fuzzy Systems.

[34]  James Lam,et al.  Fault Detection for Fuzzy Systems With Intermittent Measurements , 2009, IEEE Transactions on Fuzzy Systems.

[35]  Yu Liu,et al.  Multivariable MRAC with state feedback for output tracking , 2009, 2009 American Control Conference.

[36]  Youyi Wang,et al.  Control Synthesis of Continuous-Time T-S Fuzzy Systems With Local Nonlinear Models , 2009, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[37]  Guang-Hong Yang,et al.  Fuzzy Filter Design for Nonlinear Systems in Finite-Frequency Domain , 2010, IEEE Transactions on Fuzzy Systems.

[38]  Marcel Staroswiecki,et al.  Dynamic Output Feedback-Fault Tolerant Controller Design for Takagi–Sugeno Fuzzy Systems With Actuator Faults , 2010, IEEE Transactions on Fuzzy Systems.

[39]  Marios M. Polycarpou,et al.  Fault diagnosis of a class of nonlinear uncertain systems with Lipschitz nonlinearities using adaptive estimation , 2010, Autom..

[40]  Peng Shi,et al.  Integrated Fault Estimation and Accommodation Design for Discrete-Time Takagi–Sugeno Fuzzy Systems With Actuator Faults , 2011, IEEE Transactions on Fuzzy Systems.

[41]  Hongjiu Yang,et al.  Fault Detection for T-S Fuzzy Discrete Systems in Finite-Frequency Domain. , 2011, IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society.

[42]  Guanghong Yang,et al.  Dynamic observer-based robust control and fault detection for linear systems , 2012 .

[43]  Peng Shi,et al.  Fault Estimation Observer Design for Discrete-Time Takagi–Sugeno Fuzzy Systems Based on Piecewise Lyapunov Functions , 2012, IEEE Transactions on Fuzzy Systems.

[44]  Guang-Hong Yang,et al.  Fault Detection for T–S Fuzzy Systems With Unknown Membership Functions , 2014, IEEE Transactions on Fuzzy Systems.