Robust Filter Design in Networked Control Systems

• Author / Creator

  Allahverdi Charandabi, Behnam

• In this thesis, we study the problem of robust filtering under network-induced errors. Our intention is to design a robust filter that provides stable estimates of the plant states when the plant model is uncertain, the states are disturbed with an unknown input, and the measurements are quantized and therefore erroneous. To this end, we tackle the problem by first studying the various problems caused by the network and their effects on the filtering process when there are no model uncertainties and unknown inputs.
  Since our final design needs to be robust to unknown disturbances, we will propose two novel unknown-input linear filters, which are free of some of the restrictive assumptions seen in the literature. Both of these filters are based on a modified plant model, however, one of them has more design parameters and comes with a heavier computational burden than the other, but in return it generates slightly smoother estimates of both the states and the unknown input.
  Having two distinct classes of filters, one with the ability to estimate the network-induced errors and one capable of estimating and rejecting unknown disturbances, we next propose a two-zone robust filter, which estimates the states with limited information and under unknown disturbances. The two-zone idea is based on the fact that the error caused by a linear quantizer is significant only when the estimates are close to their real values. Taking advantage of this fact, the estimation space can be divided into two operating zones based on the reliability of the received information.
  Finally, the two-zone filter is adapted for a fault-tolerant filtering application where the measurements are assumed to undergo coarse quantization, and unknown disturbances and model uncertainties are employed to model various fault scenarios.

• Subjects / Keywords

  • Fault-Tolerant Filtering
  • Filter Design
  • Quantization
  • Networked Control Systems

• Graduation date

  Fall 2014

• Type of Item

  Thesis

• Degree

  Doctor of Philosophy

• DOI

  https://doi.org/10.7939/R3ND65

• 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.