arXiv subjects

Alexander Dorsey

Publications and source records attributed to Alexander Dorsey.

3 recordsLinked to original sources

arXiv2026

Feedback Linearization-Based Guidance with Zero-Dynamics Correction for Guaranteed Interception

This paper develops a guidance law for nonlinear interception using input-output feedback linearization (IOL). The engagement between a pursuer and an evader is modeled using point-mass dynamics, and a baseline IOL-based guidance law is constructed by regulating the angular rates of the line-of-sight (LOS) vector. While this approach yields stable input-output behavior, it does not constrain the internal (zero) dynamics of the system, which can result in non-intercepting trajectories despite successful regulation of the LOS rates. To address this limitation, a modified IOL-based guidance law is proposed that incorporates a correction mechanism to enforce convergence of the range. The resulting formulation ensures that LOS alignment corresponds to a closing trajectory, thereby enabling convergence of the pursuer to the evader for a broad class of initial engagement geometries. The proposed method retains the computational simplicity and real-time implementability of feedback linearization while improving closed-loop performance relative to classical guidance laws. Extensive Monte Carlo simulations over a wide range of initial conditions are conducted to evaluate the proposed method. The results demonstrate improved reliability, reduced miss distance, and consistent convergence compared to the baseline IOL and classical proportional navigation.

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arXiv2025

Swarm-optimized Adaptive Augmentation of Missile Autopilot

This paper considers the problem of optimizing a missile autopilot. In particular, the paper investigates the application of an online learning technique to learn and optimize the gains of a three-loop topology autopilot for a planar missile modeled with nonlinear dynamics and nonlinear aerodynamics forces and moments. The classical autopilot for a missile is based on a three-loop topology, where each loop consists of tunable proportional gains. An adaptive three-loop autopilot is constructed by augmenting the classical autopilot's fixed-gain controllers with a learning-based controller, which is recursively optimized using retrospective cost optimization. Numerical simulations show that online learning improves the tracking performance of the classical autopilot in both nominal and off-nominal interception scenarios.

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arXiv2025

Feedback Linearization-based Guidance Law for Guaranteed Interception

This paper presents an input-output feedback linearization (IOL)-based guidance law to ensure interception in a pursuer-evader engagement scenario. A point-mass dynamic model for both the pursuer and the evader is considered. An IOL guidance law is derived using range and line-of-sight (LOS) rate measurements. It is found that the range-based IOL guidance law exhibits a singularity under certain conditions. To address this issue, a fuzzy logic system is employed to smoothly blend the IOL guidance with the classical proportional guidance law, thereby avoiding the singularity. In contrast, the LOS-based IOL guidance law is free of singularities but suffers from divergence issues due to angle-related complications. To resolve this, a simple correction function is introduced to ensure consistent interception behavior. Results from Monte Carlo simulations indicate that both modifications of the IOL guidance laws cause interception with control limits applied.

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