Uncertain, Data-Driven Observer-based Feedback Control of Unmanned Aerospace Systems

Abstract

The long-term goal of this project is to construct a DDDAS framework for dynamic, data-driven sampling and control by autonomous unmanned aerospace systems using a principled approach to dynamic output feedback with theoretical justification. The specific research objective is to apply tools from nonlinear control, engineering and fluid dynamics, estimation theory, and uncertainty quantification to solve the problem of adaptive sampling of continuous and discrete processes with autonomous flight vehicles using Bayesian observer feedback. The technical approach to reach this objective is (1) to construct a principled framework for data-driven sampling of continuous and discrete spatiotemporal processes using the concept of augmented observability to guide measurement collection; (2) perform nonlinear systems analysis of the stability and optimality properties of uncertain, output-feedback control systems using dynamic, non-Gaussian observers.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jun 21, 2021
Accession Number
AD1140363

Entities

People

  • Derek Paley

Organizations

  • University of Maryland

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Space

DTIC Thesaurus Topics

  • Aerospace Craft
  • Aircrafts
  • Algorithms
  • Closed Loop Systems
  • Computational Complexity
  • Computational Fluid Dynamics
  • Computational Science
  • Control Systems
  • Differential Equations
  • Eigenvalues
  • Filtration
  • Fluid Dynamics
  • Gaussian Distributions
  • Gaussian Processes
  • Geography
  • Geometry
  • Kalman Filters
  • Linear Systems
  • Mathematical Filters
  • Molecular Dynamics
  • Nonlinear Dynamics
  • Nonlinear Systems
  • Steady State

Fields of Study

  • Computer science

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Distributed Systems and Data Platform Development

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms
  • Autonomy
  • Autonomy - Autonomous System Control
  • Space
  • Space - Spacecraft Maneuvers