Date of Award
Spring 2026
Embargo Period
1-1-2027
Access Type
Dissertation - Open Access
Degree Name
Doctor of Philosophy in Aerospace Engineering
Department
Aerospace Engineering
Committee Chair
Kadriye Merve Dogan
Committee Chair Email
dogank@erau.edu
Committee Advisor
Kadriye Merve Dogan
Committee Advisor Email
dogank@erau.edu
First Committee Member
Richard Prazenica
First Committee Member Email
prazenir@erau.edu
Second Committee Member
Dongeun Seo
Second Committee Member Email
seod@erau.edu
Third Committee Member
Sergey V. Drakunov
Third Committee Member Email
drakunov@erau.edu
Fourth Committee Member
Benjamin Gruenwald
Fourth Committee Member Email
benjamin.c.gruenwald.civ@army.mil
College Dean
James W. Gregory
Abstract
Model reference adaptive control (MRAC) is a well-established control design framework for ensuring closed-loop system stability and reference tracking performance in dynamical systems with uncertainties. Nominal, fixed-gain controllers rely on accurate mathematical models to guarantee desired stability and performance. However, uncertainty in system modeling is unavoidable. MRAC provides flexibility in system modeling, allowing modeling inaccuracies to exist under certain conditions. The learning mechanism of MRAC allows gains or uncertain parameters to be estimated online to ensure that the reference tracking objective is achieved. As with any control architecture, MRAC is theoretically sound. However, these theoretical guarantees are not always directly translatable to implementation because of the need for continuous-time to discrete-time transformations. Continuous-time control algorithms are usually sampled at very high frequencies to preserve accuracy, which requires high-performance hardware. In many real-world embedded systems, many factors contribute to the limitations of low-performance hardware, which pose a challenge for accurately implementing continuous-time controllers. Alternatively, control design can be accomplished in the discrete-time domain using an approach referred to as digital control. In digital control, system dynamics are discretized before the control design, resulting in an inherently sampled control algorithm that is readily implementable on hardware and preserves theoretical stability guarantees. Due to this advantage, the sampling frequency is allowed to be much lower than that required for continuous-time implementations. While advantageous from an implementation point of view, digital control design comes with the major drawback of difficulties in the stability analysis. This dissertation investigates several digital control design approaches for MRAC algorithms originally developed in the continuous-time settings. A rigorous Lyapunov stability analysis accompanies the solution to each control design problem, and numerical simulations provide illustrations of the control designs' capabilities.
Scholarly Commons Citation
Sisson, Nathaniel, "On the Stability and Robustness of Discrete Uncertain Systems" (2026). Doctoral Dissertations and Master's Theses. 989.
https://commons.erau.edu/edt/989
