1,960 research outputs found
Time-Constrained Temporal Logic Control of Multi-Affine Systems
In this paper, we consider the problem of controlling a dynamical system such
that its trajectories satisfy a temporal logic property in a given amount of
time. We focus on multi-affine systems and specifications given as
syntactically co-safe linear temporal logic formulas over rectangular regions
in the state space. The proposed algorithm is based on the estimation of time
bounds for facet reachability problems and solving a time optimal reachability
problem on the product between a weighted transition system and an automaton
that enforces the satisfaction of the specification. A random optimization
algorithm is used to iteratively improve the solution
Reachability in Biochemical Dynamical Systems by Quantitative Discrete Approximation (extended abstract)
In this paper, a novel computational technique for finite discrete
approximation of continuous dynamical systems suitable for a significant class
of biochemical dynamical systems is introduced. The method is parameterized in
order to affect the imposed level of approximation provided that with
increasing parameter value the approximation converges to the original
continuous system. By employing this approximation technique, we present
algorithms solving the reachability problem for biochemical dynamical systems.
The presented method and algorithms are evaluated on several exemplary
biological models and on a real case study.Comment: In Proceedings CompMod 2011, arXiv:1109.104
Traffic Network Control from Temporal Logic Specifications
We propose a framework for generating a signal control policy for a traffic
network of signalized intersections to accomplish control objectives
expressible using linear temporal logic. By applying techniques from model
checking and formal methods, we obtain a correct-by-construction controller
that is guaranteed to satisfy complex specifications. To apply these tools, we
identify and exploit structural properties particular to traffic networks that
allow for efficient computation of a finite state abstraction. In particular,
traffic networks exhibit a componentwise monotonicity property which allows
reach set computations that scale linearly with the dimension of the continuous
state space
IST Austria Thesis
Hybrid automata combine finite automata and dynamical systems, and model the interaction of digital with physical systems. Formal analysis that can guarantee the safety of all behaviors or rigorously witness failures, while unsolvable in general, has been tackled algorithmically using, e.g., abstraction, bounded model-checking, assisted theorem proving.
Nevertheless, very few methods have addressed the time-unbounded reachability analysis of hybrid automata and, for current sound and automatic tools, scalability remains critical. We develop methods for the polyhedral abstraction of hybrid automata, which construct coarse overapproximations and tightens them incrementally, in a CEGAR fashion. We use template polyhedra, i.e., polyhedra whose facets are normal to a given set of directions.
While, previously, directions were given by the user, we introduce (1) the first method
for computing template directions from spurious counterexamples, so as to generalize and
eliminate them. The method applies naturally to convex hybrid automata, i.e., hybrid
automata with (possibly non-linear) convex constraints on derivatives only, while for linear
ODE requires further abstraction. Specifically, we introduce (2) the conic abstractions,
which, partitioning the state space into appropriate (possibly non-uniform) cones, divide
curvy trajectories into relatively straight sections, suitable for polyhedral abstractions.
Finally, we introduce (3) space-time interpolation, which, combining interval arithmetic
and template refinement, computes appropriate (possibly non-uniform) time partitioning
and template directions along spurious trajectories, so as to eliminate them.
We obtain sound and automatic methods for the reachability analysis over dense
and unbounded time of convex hybrid automata and hybrid automata with linear ODE.
We build prototype tools and compare—favorably—our methods against the respective
state-of-the-art tools, on several benchmarks
A Massive Data Parallel Computational Framework for Petascale/Exascale Hybrid Computer Systems
Heterogeneous systems are becoming more common on High Performance Computing
(HPC) systems. Even using tools like CUDA and OpenCL it is a non-trivial task
to obtain optimal performance on the GPU. Approaches to simplifying this task
include Merge (a library based framework for heterogeneous multi-core systems),
Zippy (a framework for parallel execution of codes on multiple GPUs), BSGP (a
new programming language for general purpose computation on the GPU) and
CUDA-lite (an enhancement to CUDA that transforms code based on annotations).
In addition, efforts are underway to improve compiler tools for automatic
parallelization and optimization of affine loop nests for GPUs and for
automatic translation of OpenMP parallelized codes to CUDA.
In this paper we present an alternative approach: a new computational
framework for the development of massively data parallel scientific codes
applications suitable for use on such petascale/exascale hybrid systems built
upon the highly scalable Cactus framework. As the first non-trivial
demonstration of its usefulness, we successfully developed a new 3D CFD code
that achieves improved performance.Comment: Parallel Computing 2011 (ParCo2011), 30 August -- 2 September 2011,
Ghent, Belgiu
Symbolic models for nonlinear control systems without stability assumptions
Finite-state models of control systems were proposed by several researchers
as a convenient mechanism to synthesize controllers enforcing complex
specifications. Most techniques for the construction of such symbolic models
have two main drawbacks: either they can only be applied to restrictive classes
of systems, or they require the exact computation of reachable sets. In this
paper, we propose a new abstraction technique that is applicable to any smooth
control system as long as we are only interested in its behavior in a compact
set. Moreover, the exact computation of reachable sets is not required. The
effectiveness of the proposed results is illustrated by synthesizing a
controller to steer a vehicle.Comment: 11 pages, 2 figures, journa
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