Research into coordinating sensing, control and computations for autonomous vehicles
Abstract
The proposed research will advance algorithms for coordinating sensing, estimation, control and computations in systems that must operate autonomously and satisfy constraints. The effectiveness of the proposed algorithms will be demonstrated in simulation case studies for autonomous spacecraft. The proposed research into integrating sensing, estimation and control will include extending the virtual net framework for constrained maneuvering to (1) accommodate state estimation errors in the output (rather than full state) measurement case, (2) handle disjunctive sensing and control requirements when simultaneous sensing and actuation cannot be performed, and (3) incorporate inputs that enhance excitation and parameter estimate convergence performance. The proposed research into integrating control and computations will lead to reference governor strategies for adjusting set-point commands to inner loop Model Predictive (MPC) controllers which ensure that a feasible solution to MPC optimization problem is found within available computing time. Simulation case studies for control of spacecraft relative motion and for control of spacecraft attitude will be used for demonstration of the developed algorithms. Novel theory, methods, algorithms and design procedures, relevant models and prototype software implementations will be developed. The final report and at least one conference publication will be generated as an outcome of this research.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jul 25, 2019
- Source ID
- FA94531810010
Entities
People
- Ilya Vladimir
Organizations
- Air Force Research Laboratory
- Board of Regents of the University of Michigan
- United States Air Force