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Distributed Fault Diagnosis of Interconnected Nonlinear Uncertain Systems

Zhang, Qi
http://rave.ohiolink.edu/etdc/view?acc_num=wright1377888655

Abstract Details

2013, Doctor of Philosophy (PhD), Wright State University, Engineering PhD.
Fault diagnosis is crucial in achieving safe and reliable operations of interconnected control systems. This dissertation presents a distributed fault detection and isolation (FDI) method for interconnected nonlinear uncertain systems. The contributions of this dissertation include the following: First, the detection and isolation problem of process faults in a class of interconnected input-output nonlinear uncertain systems is investigated. A novel fault detection and isolation scheme is devised, and the fault detectability and isolability conditions are rigorously investigated, characterizing the class of faults in each subsystem that are detectable and isolable by the proposed distributed FDI method. Second, a distributed sensor fault FDI scheme is developed in a class of interconnected input-output nonlinear systems where only the measurable part of state variables are directly affected by the interconnections between subsystems. A class of multimachine power systems is used as an application example to illustrate the effectiveness of the proposed approach. Third, the previous results are extended to a class of interconnected input-output nonlinear systems where both the unknown and the measurable part of system states of each subsystem are directly affected by the interconnections between subsystems. In this case, the fault propagation effect among subsystems directly affects the unknown part of state variables of each subsystem. Thus, the problem considered is more challenging than what is described above. Finally, a fault detection scheme is presented for a more general distributed nonlinear systems. With a removal of a restrictive limitation on the system model structure, the results described above are extended to a class of interconnected nonlinear uncertain systems with a more general structure. In addition, the effectiveness of the above fault diagnosis schemes is illustrated by using simulations of interconnected inverted pendulums mounted on carts and multi-machine power systems. Different fault scenarios are considered to verify the diagnosis performances, and the satisfactory performances of the proposed diagnosis scheme are validated by the good simulation results. Some interesting future research work is also discussed.
Xiaodong Zhang, Ph.D. (Committee Chair)
Kuldip Rattan, Ph.D. (Committee Member)
Raul Ordonez, Ph.D. (Committee Member)
Mark Mears, Ph.D. (Committee Member)
Zhiqiang Wu, Ph.D. (Committee Member)
177 p.
Electrical Engineering
fault diagnosis; interconnected systems; adaptive learning

Recommended Citations

Citations

  • Zhang, Q. (2013). Distributed Fault Diagnosis of Interconnected Nonlinear Uncertain Systems [Doctoral dissertation, Wright State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=wright1377888655

    APA Style (7th edition)

  • Zhang, Qi. Distributed Fault Diagnosis of Interconnected Nonlinear Uncertain Systems. 2013. Wright State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=wright1377888655.

    MLA Style (8th edition)

  • Zhang, Qi. "Distributed Fault Diagnosis of Interconnected Nonlinear Uncertain Systems." Doctoral dissertation, Wright State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=wright1377888655

    Chicago Manual of Style (17th edition)

wright1377888655
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© 2013, all rights reserved.
This open access ETD is published by Wright State University and OhioLINK.