2025/09/08 by Tanay Kumar, Kumar, Tanay, Raktim Bhattacharya +1
Computer Science · Engineering · #FOS: Mathematics #Guidance and Control Systems #Optimization and Control (math.OC) #Robotic Path Planning Algorithms #Spacecraft Dynamics and Control
paper · pdf · doi:10.48550/arxiv.2509.06317
openalex publication_date 2025/09/08 · openalex created_date 2025/10/11 · openalex updated_date 2026/07/28
Navigation in the cislunar domain presents significant challenges due to chaotic and unmodeled dynamics, as well as state-dependent sensor errors. This paper develops a robust estimation framework based on Linear Fractional Transformation (LFT) models, and state estimation in H_∞ and μ synthesis framework to address these challenges. The cislunar dynamics are embedded into an LFT form that captures nonlinearities in the gravitational model and state-dependent sensor errors as structured uncertainty. A nonlinear estimator is then synthesized in the H_∞ sense to ensure robust performance guarantees in the presence of the stated uncertainties. Simulation results demonstrate the effectiveness of the estimator for navigation in a surveillance constellation.