Nonlinear Robust Observers for Simultaneous State and Fault Estimation

• Author / Creator

  Raoufi, Reza

• A fault in the system operation is deemed to occur when the system practically
  experiences an abnormal condition, such as a malfunction in the actuators/sensors. Hence,
  detection and isolation of the faulty components is crucial in control applications.
  Effective control and monitoring of a system requires accurate information of internal
  behaviour of the system. This internal behaviour can be analyzed by system's states.
  Practically, in many real systems, state space variables are not fully available for
  measurements. The two critical problems stated have motivated significant research work
  in the area of robust state and fault estimation. Fault reconstruction and estimation is
  regarded as a stronger extension to fault detection and isolation (FDI) since accurate
  fault estimation automatically implies fault detection.

  It is well known that two promising control strategies to cope with uncertain control
  processes are Hinfinity Control and Sliding Mode Control. Therefore, in this PhD thesis,
  we employ these tools and we propose observer based robust fault reconstruction (RFR) by
  integrating Hinfinity filtering and Sliding Mode Control. We also employ adaptive
  control on the sliding motion to deal with faults with unknown bounds. Another open
  problem in the context of FDI and RFR is due to systems with multiple faults at different
  system's components since it is often the case where actuators and also sensors suffer
  from faults during the course of the system's operation. Both actuators and sensors can
  suffer from faults either alone, at separate times or simultaneously. The co-existence of
  unknown fault at both sensor(s) and actuator(s) has not been addressed in any earlier
  design of fault reconstruction schemes. In this Thesis, inspired by the theory of
  singular systems, we aim at solving this problem. A New structure for reduced-order
  unknown input observers (UIOs) with application to chaotic communication and sensor fault
  reconstruction is also proposed.

• Subjects / Keywords

  • Robust Observers, Nonlinear Lipschitz Systems, Fault Estimation

• Graduation date

  Spring 2010

• Type of Item

  Thesis

• Degree

  Doctor of Philosophy

• DOI

  https://doi.org/10.7939/R31Q4X

• License

  This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.