Reachability Analysis of Large Linear Systems with Uncertain Inputs in the Krylov Subspace

12/01/2017
by   Matthias Althoff, et al.
0

One often wishes for the ability to formally analyze large-scale systems---typically, however, one can either formally analyze a rather small system or informally analyze a large-scale system. This work tries to further close this performance gap for reachability analysis of linear systems. Reachability analysis can capture the whole set of possible solutions of a dynamic system and is thus used to prove that unsafe states are never reached; this requires full consideration of arbitrarily varying uncertain inputs, since sensor noise or disturbances usually do not follow any patterns. We use Krylov methods in this work to compute reachable sets for large-scale linear systems. While Krylov methods have been used before in reachability analysis, we overcome the previous limitation that inputs must be (piecewise) constant. As a result, we can compute reachable sets of systems with several thousand state variables for bounded, but arbitrarily varying inputs, as demonstrated using a bridge model subject to disturbances.

READ FULL TEXT
research
11/05/2022

Geometry of VAS reachability sets

Vector Addition Systems (VAS) or equivalently petri-nets are a popular m...
research
10/03/2022

The Geometry of Reachability in Continuous Vector Addition Systems with States

We study the geometry of reachability sets of continuous vector addition...
research
02/19/2018

On the Decidability of Reachability in Linear Time-Invariant Systems

We consider the decidability of state-to-state reachability in linear ti...
research
06/22/2020

Adaptive Parameter Tuning for Reachability Analysis of Linear Systems

Despite the possibility to quickly compute reachable sets of large-scale...
research
04/04/2018

Numerical Verification of Affine Systems with up to a Billion Dimensions

Affine systems reachability is the basis of many verification methods. W...
research
01/29/2020

Higher Order Method for Differential Inclusions

Uncertainty is unavoidable in modeling dynamical systems and it may be r...
research
11/02/2021

Conservative Time Discretization: A Comparative Study

We present the first review of methods to overapproximate the set of rea...

Please sign up or login with your details

Forgot password? Click here to reset