Masters Theses

He Li

Keywords and Phrases

Iterative Learning Control; Kalman Filtering; Switched System

Abstract

“Switching is not an uncommon phenomenon in practical systems and processes, for examples, power switches opening and closing, transmissions lifting from low gear to high gear, and air planes crossing different layers in air. Switching can be a disaster to a system since frequent switching between two asymptotically stable subsystems may result in unstable dynamics. On the contrary, switching can be a benefit to a system since controlled switching is sometimes imposed by the designers to achieve desired performance. This encourages the study of system dynamics and performance when undesired switching occurs or controlled switching is imposed. In this research, the controlled switching is applied to an estimation process and a multivariable Iterative Learning Control (ILC) system, and system stability as well as system performance under switching are investigated. The first article develops a controlled switching strategy for the estimation of a temporal shift in a Laser Tracker (LT). For some reason, the shift cannot be measured at all time. Therefore, a model-based predictor is adopted for estimation when the measurement is not available, and a Kalman Filter (KF) is used to update the estimate when the measurement is available. With the proposed method, the estimation uncertainty is always bounded within two predefined boundaries. The second article develops a controlled switching method for multivariable ILC systems where only partial outputs are measured at a time. Zero tracking error cannot be achieved for such systems using standard ILC due to incomplete knowledge of the outputs. With the developed controlled switching, all the outputs are measured in a sequential order, and, with each currently-measured output, the standard ILC is executed. Conditions under which zero convergent tracking error is accomplished with the proposed method are investigated. The proposed method is finally applied to solving a multi-agent coordination problem”--Abstract, page iv.

Advisor(s)

Bristow, Douglas A.
Landers, Robert G.

Committee Member(s)

Balakrishnan, S. N.

Department(s)

Mechanical and Aerospace Engineering

Degree Name

M.S. in Mechanical Engineering

Comments

The author would like to gratefully acknowledge those agencies funding my research, including National Science Foundation (CMMI-1335340), the Department of the Army through the Digital Manufacturing and Design Innovation Institute (DMDII15-07-01), the Center for Aerospace Manufacturing Technologies and the Intelligent System Center at the Missouri University of Science and Technology.

Research Center/Lab(s)

Intelligent Systems Center

Publisher

Missouri University of Science and Technology

Publication Date

Summer 2019

Journal article titles appearing in thesis/dissertation

  • A switched estimation strategy based on Kalman filtering for compensating laser tracker ADM shift
  • Iterative learning control for multivariable systems with switching outputs and application to multi-agent coordination

Pagination

xii, 94 pages

Note about bibliography

Includes bibliographic references.

Rights

© 2019 He Li, All rights reserved.

Document Type

Thesis - Open Access

File Type

text

Language

English

Thesis Number

T 12088

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