Doctoral Dissertations

Abdul Ghafoor

Keywords and Phrases

Adaptive Controls; Automatic Controls; Event-Triggered Control; Neural network Control; Observer and Estimation Theory; Set-Theoretic Control

Abstract

"In this study, several new observer-based event-triggered and set-theoretic control schemes are presented to advance the state of the art in neuro-adaptive controls. In the first part, six new event-triggered neuro-adaptive control (ETNAC) schemes are presented for uncertain linear systems. These comprehensive designs offer flexibility to choose a design depending upon system performance requirements. Stability proofs for each scheme are presented and their performance is analyzed using benchmark examples. In the second part, the scope of the ETNAC is extended to uncertain nonlinear systems. It is applied to a case of precision formation flight of the microsatellites at the Sun-Earth/Moon L1 libration point. This dynamic system is selected to evaluate the performance of the ETNAC techniques in a setting that is highly nonlinear and chaotic in nature. Moreover, factors like restricted controls, response to uncertainties and jittering makes the controller design even trickier for maintaining a tight formation precision. Lyapunov function-based stability analysis and numerical results are presented. Note that most real-world systems involve constraints due to hardware limitations, disturbances, uncertainties, nonlinearities, and cannot always be efficiently controlled by using linearized models. To address all these issues simultaneously, a barrier Lyapunov function-based control architecture called the segregated prescribed performance guaranteeing neuro-adaptive control is developed and tested for the constrained uncertain nonlinear systems, in the third part. It guarantees strict performance that can be independently prescribed for each individual state and/or error signal of the given system. Furthermore, the proposed technique can identify unknown dynamics/uncertainties online and provides a way to regulate the control input"--Abstract, page iv.

Advisor(s)

Balakrishnan, S. N.

Committee Member(s)

Sarangapani, Jagannathan, 1965-
Pernicka, Henry J.
Krishnamurthy, K.
Yucelen, Tansel

Department(s)

Mechanical and Aerospace Engineering

Degree Name

Ph. D. in Mechanical Engineering

Sponsor(s)

United States. National Aeronautics and Space Administration

Comments

This research was supported in part by the National Aeronautics and Space Administration under Grant NNX15AM51A and NNX15AN04A.

Publisher

Missouri University of Science and Technology

Publication Date

Spring 2020

Journal article titles appearing in thesis/dissertation

  • Design and analysis of event-triggered neuro-adaptive controller (ETNAC) for uncertain systems
  • Event-triggered neuro-adaptive control for formation control with reduced jitter in a deep space environment
  • Segregated prescribed performance guaranteeing neuro-adaptive controller (SPPGNAC) for constrained uncertain nonlinear systems

Pagination

xvi, 184 pages

Note about bibliography

Includes bibliographic references.

Rights

© 2020 Abdul Ghafoor, All rights reserved.

Document Type

Dissertation - Open Access

File Type

text

Language

English

Thesis Number

T 11676

Electronic OCLC #

1164718930

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