Title
Linear Hybrid System Falsification Through Descent
Abstract
In this paper, we address the problem of local search for the falsification of hybrid automata with affine dynamics. Namely, if we are given a sequence of locations and a maximum simulation time, we return the trajectory that comes the closest to the unsafe set. In order to solve this problem, we formulate it as a differentiable optimization problem which we solve using Sequential Quadratic Programming. The purpose of developing such a local search method is to combine it with high level stochastic optimization algorithms in order to falsify hybrid systems with complex discrete dynamics and high dimensional continuous spaces. Experimental results indicate that indeed the local search procedure improves upon the results of pure stochastic optimization algorithms.
Year
Venue
Keywords
2011
Clinical Orthopaedics and Related Research
hybrid system
Field
DocType
Volume
Affine transformation,Stochastic optimization,Mathematical optimization,Automaton,Algorithm,Differentiable function,Local search (optimization),Sequential quadratic programming,Hybrid system,Optimization problem,Mathematics
Journal
abs/1105.1
Citations 
PageRank 
References 
4
0.46
15
Authors
2
Name
Order
Citations
PageRank
Houssam Abbas19016.31
Georgios E. Fainekos280452.65