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20242026
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eess.SY2026

Experimental Demonstration of a Decentralized Electromagnetic Formation Flying Control Using Alternating Magnetic Field Forces

Sumit S. Kamat, Ajin Sunny, T. Michael Seigler +1

Electromagnetic formation flying (EMFF) is challenging due to the complex coupling between the electromagnetic fields generated by each satellite in the formation. To address this…

eess.SY2026

Predicted-Flow Control Barrier Functions for Real-Time Safe Optimal Control

Amirsaeid Safari, Jesse B. Hoagg

Control barrier functions (CBFs) provide real-time safety guarantees through pointwise conditions on the state. However, synthesizing a valid CBF is difficult and the resulting con…

eess.SY2026

Receding-Horizon Nonlinear Optimal Control With Safety Constraints Using Constrained Approximate Dynamic Programming

Ricardo Gutierrez, Jesse B. Hoagg

We present a receding-horizon optimal control for nonlinear continuous-time systems subject to state constraints. The cost is a quadratic finite-horizon integral. The key enabling…

eess.SY2026

Safe Landing on Small Celestial Bodies with Gravitational Uncertainty Using Disturbance Estimation and Control Barrier Functions

Felipe Arenas-Uribe, T. Michael Seigler, Jesse B. Hoagg

Soft landing on small celestial bodies (SCBs) poses unique challenges, as gravitational models poorly characterize the higher-order gravitational effects of SCBs. Existing control…

eess.SY20251 cited

Electromagnetic Formation Flying Using Alternating Magnetic Field Forces and Control Barrier Functions for State and Input Constraints

Sumit S. Kamat, T. Michael Seigler, Jesse B. Hoagg

This article presents a feedback control algorithm for electromagnetic formation flying with constraints on the satellites' states and control inputs. The algorithm combines severa…

eess.SY2025

Control Barrier Functions With Real-Time Gaussian Process Modeling

Ricardo Gutierrez, Jesse B. Hoagg

We present an approach for satisfying state constraints in systems with nonparametric uncertainty by estimating this uncertainty with a real-time-update Gaussian process (GP) model…