Author

Polk Yu

Date of Award

2025

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Electrical and Computer Engineering

Committee Chair

Laurie Joiner

Committee Member

Farbod Fahimi

Committee Member

Shangbing Ai

Committee Member

Avimanyu Sahoo

Research Advisor

Yuri Shtessel

Subject(s)

Guided missiles--Control systems, Guidance systems (Flight), Sliding mode control, Hypersonic aerodynamics

Abstract

This research is focused on the study of the trajectory tracking of a Hypersonic Missile (HM) in its terminal phase of flight in light of the cross coupling, high nonlinearity, and uncertainty in the missile dynamics. This is coupled with unmatched disturbances and perturbations that all need to be compensated for in a really short time. In this research, a relative degree approach is utilized to design an adaptive higher order sliding mode control (AHOSM) for controlling the nonlinear perturbed HM. This technique allows for the proposed observation/differentiation/control (autopilot) algorithms equipped with adaptation capabilities to be employed for designing the HM integrated guidance and autopilot. This research develops each portion of the proposed algorithm and the corresponding differentiator settling time estimation. The HOSM observer exactly estimates the perturbations which is used by the controller to cancel out the nonlinear perturbations. An adaptive nonlinear continuous finite time convergent control algorithm is used in conjunction with HOSM differentiators to control the system response to track the desired terminal phase trajectory. The double-layer adaptive algorithm is based on equivalent control concept and does not allow overestimation of the control gains which mitigates control chattering and yields control continuity. Fixed convergence time estimation is achieved independent of initial conditions of the differentiation errors. The robustness and high accuracy output tracking in the presence of matched and unmatched external disturbances and missile model uncertainties is demonstrated for both the differentiator and controller via Monte Carlo simulations.

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