Scalable Control and Verification with Compositional, Hierarchical and Learning-Based Methods
Abstract
This project will develop scalable control and verifcation tools for systems with high dimensional, nonlinear, uncertain dynamics, and complex requirements. It willachieve scalability with a conuence of compositional, hierarchical and learning-basedapproaches. The compositional approach exposes a large system as an interconnectionof smaller subsystems and derives system-level guarantees from appropriate abstractionsof the subsystems. The hierarchical approach decomposes the synthesis and verification tasks into layers, from high-level decision making to low-level control synthesis.Taken together, these approaches break apart intractable problems into subproblemsof manageable size. In addition they provide the designer with modularity, as inter-faces between subsystems and layers demarcate the system into components that canbe modified individually while preserving high-level guarantees.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Mar 07, 2023
- Source ID
- FA95502110288
Entities
People
- Murat Arcak
Organizations
- Air Force Office of Scientific Research
- United States Air Force
- University of California Regents