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Chance-Constrained Stochastic MPC to Deterministic Second-Order Cone Programming Equivalents for Lossy Satellite Links
Subject area: Science,Engineering and Technology · Area of research: UTM / Satellite Communications / Control Systems
Abstract
Unmanned aerial vehicle navigation under lossy satellite backhauls demands robust probabilistic safety guarantees. This paper introduces a rigorous chance-constrained Model Predictive Control (MPC) framework that reformulates stochastic collision avoidance into deterministic Second-Order Cone Programming (SOCP) equivalents. By integrating satellite-terrestrial telemetry via NigComSat-1R parameters, the proposed architecture guarantees recursive feasibility and robust collision avoidance within 4D Cylindrical Volume Exclusion (CVE) models under packet jitter, Age-of-Information (AoI) degradation, and telemetry latency. Comprehensive MATLAB numerical simulations validate that the derived SOCP formulation maintains strict spatial safety margins under severe packet dropout rates while satisfying real-time onboard solver execution limits. Ultimately, this approach provides a reliable paradigm shift for sub-national Unmanned Traffic Management (UTM) airspace integration.
Keywords
second-order cone programming; stochastic model predictive control; unmanned traffic management; satellite communications; age of information
References
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How to cite this paper
@article{1724639,
author = {Anyanwu Obioma Anselam, Patrick U. Anyanwu, Engr. Dr. Emmanuel Nnali-Uroh, Ijeoma Precious Ugwu; Esther Nwachukwu, Ibe Tochukwu Cosmas; Okolie Chukwuemeka Anselm},
title = {Chance-Constrained Stochastic MPC to Deterministic Second-Order Cone Programming Equivalents for Lossy Satellite Links},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {10},
number = {5},
pages = {501-504},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1724639.pdf},
abstract = {Unmanned aerial vehicle navigation under lossy satellite backhauls demands robust probabilistic safety guarantees. This paper introduces a rigorous chance-constrained Model Predictive Control (MPC) framework that reformulates stochastic collision avoidance into deterministic Second-Order Cone Programming (SOCP) equivalents. By integrating satellite-terrestrial telemetry via NigComSat-1R parameters, the proposed architecture guarantees recursive feasibility and robust collision avoidance within 4D Cylindrical Volume Exclusion (CVE) models under packet jitter, Age-of-Information (AoI) degradation, and telemetry latency. Comprehensive MATLAB numerical simulations validate that the derived SOCP formulation maintains strict spatial safety margins under severe packet dropout rates while satisfying real-time onboard solver execution limits. Ultimately, this approach provides a reliable paradigm shift for sub-national Unmanned Traffic Management (UTM) airspace integration.},
keywords = {second-order cone programming; stochastic model predictive control; unmanned traffic management; satellite communications; age of information},
month = {November},
}