9,427 research outputs found
Lyapunov-Barrier Characterization of Robust Reach-Avoid-Stay Specifications for Hybrid Systems
Stability, reachability, and safety are crucial properties of dynamical
systems. While verification and control synthesis of reach-avoid-stay
objectives can be effectively handled by abstraction-based formal methods, such
approaches can be computationally expensive due to the use of state-space
discretization. In contrast, Lyapunov methods qualitatively characterize
stability and safety properties without any state-space discretization. Recent
work on converse Lyapunov-barrier theorems also demonstrates an approximate
completeness or verifying reach-avoid-stay specifications of systems modelled
by nonlinear differential equations. In this paper, based on the topology of
hybrid arcs, we extend the Lyapunov-barrier characterization to more general
hybrid systems described by differential and difference inclusions. We show
that Lyapunov-barrier functions are not only sufficient to guarantee
reach-avoid-stay specifications for well-posed hybrid systems, but also
necessary for arbitrarily slightly perturbed systems under mild conditions.
Numerical examples are provided to illustrate the main results
Formal Controller Synthesis from Specifications Given by Discrete-Time Hybrid Automata
This paper deals with formal controller synthesis for discrete-time dynamical systems. For a specification under the form of a discrete-time hybrid automaton, we aim at synthesizing controllers such that the trajectories of the closed-loop system are also trajectories of the hybrid automaton. We first show that the existence of an alternating simulation relation from the specification to the open-loop system is a necessary and sufficient condition for the existence of such controllers. Then, we propose an approach based on the use of symbolic (i.e. finite-state) abstractions of both the system and the specification. Effective computations are discussed for systems that are monotone and for specifications given by piecewise affine hybrid automata. We extend our approach to handle specifications with additional safety or reachability requirements. Finally, we illustrate our approach with examples from autonomous vehicle control
Sapo: Reachability Computation and Parameter Synthesis of Polynomial Dynamical Systems
Sapo is a C++ tool for the formal analysis of polynomial dynamical systems.
Its main features are: 1) Reachability computation, i.e., the calculation of
the set of states reachable from a set of initial conditions, and 2) Parameter
synthesis, i.e., the refinement of a set of parameters so that the system
satisfies a given specification. Sapo can represent reachable sets as unions of
boxes, parallelotopes, or parallelotope bundles (symbolic representation of
polytopes). Sets of parameters are represented with polytopes while
specifications are formalized as Signal Temporal Logic (STL) formulas
Model Predictive Control for Signal Temporal Logic Specification
We present a mathematical programming-based method for model predictive
control of cyber-physical systems subject to signal temporal logic (STL)
specifications. We describe the use of STL to specify a wide range of
properties of these systems, including safety, response and bounded liveness.
For synthesis, we encode STL specifications as mixed integer-linear constraints
on the system variables in the optimization problem at each step of a receding
horizon control framework. We prove correctness of our algorithms, and present
experimental results for controller synthesis for building energy and climate
control
Contracts as specifications for dynamical systems in driving variable form
This paper introduces assume/guarantee contracts on continuous-time control
systems, hereby extending contract theories for discrete systems to certain new
model classes and specifications. Contracts are regarded as formal
characterizations of control specifications, providing an alternative to
specifications in terms of dissipativity properties or set-invariance. The
framework has the potential to capture a richer class of specifications more
suitable for complex engineering systems. The proposed contracts are supported
by results that enable the verification of contract implementation and the
comparison of contracts. These results are illustrated by an example of a
vehicle following system.Comment: 8 pages, 2 figures; minor changes in the final version, as accepted
for publication in the Proceedings of the 2019 European Control Conference,
Naples, Ital
Hybrid modeling of biological networks: mixing temporal and qualitative biological properties
<p>Abstract</p> <p>Background</p> <p>Modeling a dynamical biological system is often a difficult task since the a <it>priori </it>unknown parameters of such models are not always directly given by the experiments. Despite the lack of experimental quantitative knowledge, one can see a dynamical biological system as (i) the combined evolution tendencies (increase or decrease) of the biological compound concentrations, and: (ii) the temporal features, such as delays between two concentration peaks (i.e. the times when one of the components completes an increase (resp. decrease) phase and starts a decrease (resp. increase) phase).</p> <p>Results</p> <p>We propose herein a new hybrid modeling framework that follows such biological assumptions. This hybrid approach deals with both a qualitative structure of the system and a quantitative structure. From a theoretical viewpoint, temporal specifications are expressed as equality or inequality constraints between delay parameters, while the qualitative specifications are expressed as an ordered pattern of the concentrations peaks of the components. Using this new hybrid framework, the temporal specifications of a biological system can be obtained from incomplete experimental data. The model may be processed by a hybrid model-checker (e.g. Phaver) which is able to give some new constraints on the delay parameters (e.g. the delay for a given transition is exactly 5 hours after the later peak of a gene product concentration). Furthermore, by using a constraint solver on the previous results, it becomes possible to get the set of parameters settings which are consistent with given specifications. Such a modeling approach is particularly accurate for modeling oscillatory biological behaviors like those observed in the Drosophila circadian cycles. The achieved results concerning the parameters of this oscillatory system formally confirm the several previous studies made by numerical simulations. Moreover, our analysis makes it possible to propose an automatic investigation of the respective impact of per and tim on the circadian cycle.</p> <p>Conclusions</p> <p>A new hybrid technique for an automatic formal analysis of biological systems is developed with a special emphasis on their oscillatory behaviors. It allows the use of incomplete and empirical biological data.</p
Sciduction: Combining Induction, Deduction, and Structure for Verification and Synthesis
Even with impressive advances in automated formal methods, certain problems
in system verification and synthesis remain challenging. Examples include the
verification of quantitative properties of software involving constraints on
timing and energy consumption, and the automatic synthesis of systems from
specifications. The major challenges include environment modeling,
incompleteness in specifications, and the complexity of underlying decision
problems.
This position paper proposes sciduction, an approach to tackle these
challenges by integrating inductive inference, deductive reasoning, and
structure hypotheses. Deductive reasoning, which leads from general rules or
concepts to conclusions about specific problem instances, includes techniques
such as logical inference and constraint solving. Inductive inference, which
generalizes from specific instances to yield a concept, includes algorithmic
learning from examples. Structure hypotheses are used to define the class of
artifacts, such as invariants or program fragments, generated during
verification or synthesis. Sciduction constrains inductive and deductive
reasoning using structure hypotheses, and actively combines inductive and
deductive reasoning: for instance, deductive techniques generate examples for
learning, and inductive reasoning is used to guide the deductive engines.
We illustrate this approach with three applications: (i) timing analysis of
software; (ii) synthesis of loop-free programs, and (iii) controller synthesis
for hybrid systems. Some future applications are also discussed
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