Doctoral Dissertations


Jia Cai


"With the rapid development of modern control systems, a significant number of industrial systems may suffer from component failures. An accurate yet faster fault prognosis and resilience can improve system availability and reduce unscheduled downtime. Therefore, in this dissertation, model-based prognosis and resilience control schemes have been developed for online prediction and accommodation of faults for distributed parameter systems (DPS). First, a novel fault detection, estimation and prediction framework is introduced utilizing a novel observer for a class of linear DPS with bounded disturbance by modeling the DPS as a set of partial differential equations.

To relax the state measurability in DPS, filters are introduced to redesign the detection observer. Upon detecting a fault, an adaptive term is activated to estimate the multiplicative fault and a tuning law is derived to tune the fault parameter magnitude. Then based on this estimated fault parameter together with its failure limit, time-to-failure (TTF) is derived for prognosis. A novel fault accommodation scheme is developed to handle actuator and sensor faults with boundary measurements. Next, a fault isolation scheme is presented to differentiate actuator, sensor and state faults with a limited number of measurements for a class of linear and nonlinear DPS.

Subsequently, actuator and sensor fault detection and prediction for a class of nonlinear DPS are considered with bounded disturbance by using a Luenberger observer. Finally, a novel resilient control scheme is proposed for nonlinear DPS once an actuator fault is detected by using an additional boundary measurement. In all the above methods, Lyapunov analysis is utilized to show the boundedness of the closed-loop signals during fault detection, prediction and resilience under mild assumptions"--Abstract, page iv.


Sarangapani, Jagannathan, 1965-

Committee Member(s)

Acar, Levent
Erickson, Kelvin T.
Landers, Robert G.
Zawodniok, Maciej Jan, 1975-
Salour, Al


Electrical and Computer Engineering

Degree Name

Ph. D. in Electrical Engineering


National Science Foundation (U.S.)
Missouri University of Science and Technology. Intelligent Maintenance System Center


Missouri University of Science and Technology

Publication Date

Summer 2016

Journal article titles appearing in thesis/dissertation

  • Model-based fault detection, estimation, and prediction for a class of linear distributed parameter systems
  • Model-based fault accommodation for a class of distributed parameter systems represented by linear coupled PDE
  • Fault diagnosis in distributed parameter systems modeled by linear and nonlinear parabolic partial differential equations
  • Fault detection and prediction for a class of nonlinear distributed parameter systems with actuator or sensor faults
  • Model-based actuator fault resilient control for a class of nonlinear distributed parameter systems


xiii, 237 pages

Note about bibliography

Includes bibliographic references.


© 2016 Jia Cai, All rights reserved.

Document Type

Dissertation - Open Access

File Type




Subject Headings

Distributed parameter systems
Fault location (Engineering) -- Mathematical models

Thesis Number

T 10950

Electronic OCLC #