Integral Quadratic Constraints and Safety Certificates for Uncertainty Characterization and Control Safety-Aware Filtering of Proximity Operations Between Satellites

Techniques in robust optimization and formal verification methods are used (1) to examine the stability and robust performance of a satellite controller that considers six-dimensional, uncertain state, and often unmodeled dynamics during rendezvous and proximity operations, and (2) to explore the sy...

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Main Author: Garcia Burgos, Axel
Other Authors: Linares, Richard
Format: Thesis
Published: Massachusetts Institute of Technology 2023
Online Access:https://hdl.handle.net/1721.1/152485
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author Garcia Burgos, Axel
author2 Linares, Richard
author_facet Linares, Richard
Garcia Burgos, Axel
author_sort Garcia Burgos, Axel
collection MIT
description Techniques in robust optimization and formal verification methods are used (1) to examine the stability and robust performance of a satellite controller that considers six-dimensional, uncertain state, and often unmodeled dynamics during rendezvous and proximity operations, and (2) to explore the synthesis of control Lyapunov/barrier functions (CLFs/CBFs) using neural networks and stochastic gradient descent to provide safety-aware filtering for the fuel-optimal control policies. A linear quadratic regulator controller for a servicer satellite (Servicer) is analyzed via the dissipativity inequality principle and quadratic constraints. This method allows the capture of unmodeled dynamics to reduce system uncertainty of proximity operations among the Servicer, client satellite (Client), and unsafe regions (e.g., obstacle). The same controller is implemented with a finite time horizon (i.e., model predictive controller) to filter out unsafe control output during an autonomous inspection of a Client. This framework mitigates the collision risk based on integral quadratic constraints (IQCs) worst bounds recommendation, miss distance, Mahalanobis distance, and Probability of Collision (Pc) metrics. Innovative deterministic reachability methods based on integral quadratic constraints and neural Lyapunov functions are compared and connected. The novel contributions of this work focus on formulating mathematical safety guarantees, modeling controller output, and reducing uncertainty on system performance when designing fuel-optimal and safe maneuvers of Servicer around the Client while avoiding unsafe regions in LEO.
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spelling mit-1721.1/1524852023-10-19T03:59:01Z Integral Quadratic Constraints and Safety Certificates for Uncertainty Characterization and Control Safety-Aware Filtering of Proximity Operations Between Satellites Garcia Burgos, Axel Linares, Richard Massachusetts Institute of Technology. Department of Aeronautics and Astronautics Techniques in robust optimization and formal verification methods are used (1) to examine the stability and robust performance of a satellite controller that considers six-dimensional, uncertain state, and often unmodeled dynamics during rendezvous and proximity operations, and (2) to explore the synthesis of control Lyapunov/barrier functions (CLFs/CBFs) using neural networks and stochastic gradient descent to provide safety-aware filtering for the fuel-optimal control policies. A linear quadratic regulator controller for a servicer satellite (Servicer) is analyzed via the dissipativity inequality principle and quadratic constraints. This method allows the capture of unmodeled dynamics to reduce system uncertainty of proximity operations among the Servicer, client satellite (Client), and unsafe regions (e.g., obstacle). The same controller is implemented with a finite time horizon (i.e., model predictive controller) to filter out unsafe control output during an autonomous inspection of a Client. This framework mitigates the collision risk based on integral quadratic constraints (IQCs) worst bounds recommendation, miss distance, Mahalanobis distance, and Probability of Collision (Pc) metrics. Innovative deterministic reachability methods based on integral quadratic constraints and neural Lyapunov functions are compared and connected. The novel contributions of this work focus on formulating mathematical safety guarantees, modeling controller output, and reducing uncertainty on system performance when designing fuel-optimal and safe maneuvers of Servicer around the Client while avoiding unsafe regions in LEO. Ph.D. 2023-10-18T17:09:47Z 2023-10-18T17:09:47Z 2023-06 2023-09-20T15:13:59.788Z Thesis https://hdl.handle.net/1721.1/152485 In Copyright - Educational Use Permitted Copyright retained by author(s) https://rightsstatements.org/page/InC-EDU/1.0/ application/pdf Massachusetts Institute of Technology
spellingShingle Garcia Burgos, Axel
Integral Quadratic Constraints and Safety Certificates for Uncertainty Characterization and Control Safety-Aware Filtering of Proximity Operations Between Satellites
title Integral Quadratic Constraints and Safety Certificates for Uncertainty Characterization and Control Safety-Aware Filtering of Proximity Operations Between Satellites
title_full Integral Quadratic Constraints and Safety Certificates for Uncertainty Characterization and Control Safety-Aware Filtering of Proximity Operations Between Satellites
title_fullStr Integral Quadratic Constraints and Safety Certificates for Uncertainty Characterization and Control Safety-Aware Filtering of Proximity Operations Between Satellites
title_full_unstemmed Integral Quadratic Constraints and Safety Certificates for Uncertainty Characterization and Control Safety-Aware Filtering of Proximity Operations Between Satellites
title_short Integral Quadratic Constraints and Safety Certificates for Uncertainty Characterization and Control Safety-Aware Filtering of Proximity Operations Between Satellites
title_sort integral quadratic constraints and safety certificates for uncertainty characterization and control safety aware filtering of proximity operations between satellites
url https://hdl.handle.net/1721.1/152485
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