Date of Award:

5-2023

Document Type:

Dissertation

Degree Name:

Doctor of Philosophy (PhD)

Department:

Mechanical and Aerospace Engineering

Committee Chair(s)

David Geller

Committee

David Geller

Committee

Randy Christensen

Committee

Matt Harris

Committee

Stephen Whitmore

Committee

Greg Droge

Committee

Doug Hunsaker

Abstract

Sustained actuator saturation is a common occurrence for missile engagements. The saturation nonlinearity creates some difficulty for high-fidelity linear analysis methods. This dissertation investigates three methods of modeling actuator saturation in an advanced linear analysis. The linear covariance tools from this dissertation run extremely fast and provide several advantages over other linear missile engagement analysis methods. First, a simulation is developed and validated for a target engagement scenario without actuator saturation. Next, saturations are introduced to the problem, along with the first analysis method: statistical linear covariance analysis. This method combines the augmented state linear covariance framework with the statistical linearization technique. The second method considered is tunable linear covariance analysis. Tunable linear covariance analysis utilizes a switching parameter to determine when to switch the dynamics of the problem. The final method is called event trigger linear covariance analysis. This method involves switching GN&C modes using a constraint equation and a covariance shaping matrix. All three analysis methods are validated using Monte Carlo methods, and statistical linear covariance analysis is found to be the most robust and accurate of the three methods. This method is utilized to rapidly analyze missile engagement performance under varying levels of saturation. The parameters of the analysis include guidance laws, sensor accuracy levels, target evasive maneuvers, and actuator responsiveness.

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