Digital Twin Enabled Autonomous Control for On-Orbit Spacecraft Servicing
Abstract
This multidisciplinary program of basic and applied research addresses the challenges of autonomous on-orbit space operations. A novel program of mathematical, computational and engineering research addresses foundational challenges in 1) digital twin technology and 2) feedback control algorithms all in the context of space systems. A campaign of experimental validation and demonstration in multiple testbeds serves to integrate the research advances; validate, robustify and harden the algorithms; and enable transition of research products into DoD applications. Key novel research ideas include- 1) a probabilistic graphical model foundation for digital twins that automates model calibration and updating, makes data-model integration scalable across many assets and quantifies uncertainty; 2) new feedback control algorithms that leverage model predictive control to achieve control for on-orbit space operations under stringent constraints, and handle uncertainty by accounting for hybrid and set-valued dynamics; 3) new human-machine-aware supervisory schemes targeting uncertain and contested operating environments, synthesized as hybrid control schemes that coordinate control algorithms across different phases of the mission, address recovery from unexpected conditions, and incorporate the role of potential human intervention. Experimental demonstration in testbeds covers mission-specific features in three case studies- on-orbit assembly, decommissioning and towing, and on-orbit refueling.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Mar 14, 2024
- Source ID
- FA95502310678
Entities
People
- Ricardo G. Sanfelice
Organizations
- Air Force Office of Scientific Research
- United States Air Force
- University of California, Santa Cruz