Computation-Based Probabilistic Validation of Complex Cyber-Controlled Systems

Abstract

The project research was concerned with verification of stochastic hybrid systems with temporal logic performance specifications. The major technical theme of the research was the leveraging of the computational tools from both probabilistic physical system verification, and those of discrete system verification, to create a computationally effective and automated verification methodology. A project emphasis was on developing methods that can scale gracefully to large systems. The goals were pursued both on a theory level, developing approaches that reduce hybrid verification problems with temporal logic specifications to more tractable computations that still provide safety and performance guarantees, as well as by developing new computational and simulation algorithms that are principle-based and provide improved efficiency over those currently available. These methods include counter-example guided schemes. Also investigated were fundamental questions about the existence of verification algorithms for certain hybrid system classes. As well, part of the research involved development of new tools for the analysis of hybrid systems that specifically contain the sampling of signals, and the research resulted in significant improvements over existing methods.

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Document Details

Document Type
Technical Report
Publication Date
May 09, 2019
Accession Number
AD1085999

Entities

People

  • Geir E. Dullerud
  • Mahesh Viswanathan
  • Matthew P. West

Organizations

  • University of Illinois Urbana–Champaign

Tags

Communities of Interest

  • Cyber
  • Engineered Resilient Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Classification
  • Computational Fluid Dynamics
  • Computational Science
  • Computers
  • Control Systems
  • Differential Equations
  • Fokker Planck Equations
  • Linear Systems
  • Markov Processes
  • Model Predictive Control
  • Probabilistic Models
  • Probability
  • Probability Distributions
  • Random Variables
  • Reasoning
  • Stochastic Processes

Fields of Study

  • Computer science

Readers

  • Computational Fluid Dynamics (CFD)
  • Mathematical Modeling and Probability Theory.
  • Systems Analysis and Design

Technology Areas

  • Cyber