117 research outputs found
Safe Neighborhood Computation for Hybrid System Verification
For the design and implementation of engineering systems, performing
model-based analysis can disclose potential safety issues at an early stage.
The analysis of hybrid system models is in general difficult due to the
intrinsic complexity of hybrid dynamics. In this paper, a simulation-based
approach to formal verification of hybrid systems is presented.Comment: In Proceedings HAS 2014, arXiv:1501.0540
A Vision of Collaborative Verification-Driven Engineering of Hybrid Systems
Abstract. Hybrid systems with both discrete and continuous dynamics are an important model for real-world physical systems. The key challenge is how to ensure their correct functioning w.r.t. safety requirements. Promising techniques to ensure safety seem to be model-driven engineering to develop hybrid systems in a well-defined and traceable manner, and formal verification to prove their correctness. Their combination forms the vision of verification-driven engineering. Despite the remarkable progress in automating formal verification of hybrid systems, the construction of proofs of complex systems often requires significant human guidance, since hybrid systems verification tools solve undecidable problems. It is thus not uncommon for verification teams to consist of many players with diverse expertise. This paper introduces a verification-driven engineering toolset that extends our previous work on hybrid and arithmetic verification with tools for (i) modeling hybrid systems, (ii) exchanging and comparing models and proofs, and (iii) managing verification tasks. This toolset makes it easier to tackle large-scale verification tasks.
Collaborative Verification-Driven Engineering of Hybrid Systems
Hybrid systems with both discrete and continuous dynamics are an important
model for real-world cyber-physical systems. The key challenge is to ensure
their correct functioning w.r.t. safety requirements. Promising techniques to
ensure safety seem to be model-driven engineering to develop hybrid systems in
a well-defined and traceable manner, and formal verification to prove their
correctness. Their combination forms the vision of verification-driven
engineering. Often, hybrid systems are rather complex in that they require
expertise from many domains (e.g., robotics, control systems, computer science,
software engineering, and mechanical engineering). Moreover, despite the
remarkable progress in automating formal verification of hybrid systems, the
construction of proofs of complex systems often requires nontrivial human
guidance, since hybrid systems verification tools solve undecidable problems.
It is, thus, not uncommon for development and verification teams to consist of
many players with diverse expertise. This paper introduces a
verification-driven engineering toolset that extends our previous work on
hybrid and arithmetic verification with tools for (i) graphical (UML) and
textual modeling of hybrid systems, (ii) exchanging and comparing models and
proofs, and (iii) managing verification tasks. This toolset makes it easier to
tackle large-scale verification tasks
Efficient reachability analysis of parametric linear hybrid systems with time-triggered transitions
Efficiently handling time-triggered and possibly nondeterministic switches
for hybrid systems reachability is a challenging task. In this paper we present
an approach based on conservative set-based enclosure of the dynamics that can
handle systems with uncertain parameters and inputs, where the uncertainties
are bound to given intervals. The method is evaluated on the plant model of an
experimental electro-mechanical braking system with periodic controller. In
this model, the fast-switching controller dynamics requires simulation time
scales of the order of nanoseconds. Accurate set-based computations for
relatively large time horizons are known to be expensive. However, by
appropriately decoupling the time variable with respect to the spatial
variables, and enclosing the uncertain parameters using interval matrix maps
acting on zonotopes, we show that the computation time can be lowered to 5000
times faster with respect to previous works. This is a step forward in formal
verification of hybrid systems because reduced run-times allow engineers to
introduce more expressiveness in their models with a relatively inexpensive
computational cost.Comment: Submitte
Formal Verification of Full-Wave Rectifier: A Case Study
We present a case study of formal verification of full-wave rectifier for
analog and mixed signal designs. We have used the Checkmate tool from CMU [1],
which is a public domain formal verification tool for hybrid systems. Due to
the restriction imposed by Checkmate it necessitates to make the changes in the
Checkmate implementation to implement the complex and non-linear system.
Full-wave rectifier has been implemented by using the Checkmate custom blocks
and the Simulink blocks from MATLAB from Math works. After establishing the
required changes in the Checkmate implementation we are able to efficiently
verify the safety properties of the full-wave rectifier.Comment: The IEEE 8th International Conference on ASIC (IEEE ASICON 2009),
October 20-23 2009, Changsha, Chin
Simulator Semantics for System Level Formal Verification
Many simulation based Bounded Model Checking approaches to System Level
Formal Verification (SLFV) have been devised. Typically such approaches exploit
the capability of simulators to save computation time by saving and restoring
the state of the system under simulation. However, even though such approaches
aim to (bounded) formal verification, as a matter of fact, the simulator
behaviour is not formally modelled and the proof of correctness of the proposed
approaches basically relies on the intuitive notion of simulator behaviour.
This gap makes it hard to check if the optimisations introduced to speed up the
simulation do not actually omit checking relevant behaviours of the system
under verification.
The aim of this paper is to fill the above gap by presenting a formal
semantics for simulators.Comment: In Proceedings GandALF 2015, arXiv:1509.0685
Research Priorities for Robust and Beneficial Artificial Intelligence
Success in the quest for artificial intelligence has the potential to bring
unprecedented benefits to humanity, and it is therefore worthwhile to
investigate how to maximize these benefits while avoiding potential pitfalls.
This article gives numerous examples (which should by no means be construed as
an exhaustive list) of such worthwhile research aimed at ensuring that AI
remains robust and beneficial.Comment: This article gives examples of the type of research advocated by the
open letter for robust & beneficial AI at
http://futureoflife.org/ai-open-lette
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