652 research outputs found
Robust distributed linear programming
This paper presents a robust, distributed algorithm to solve general linear
programs. The algorithm design builds on the characterization of the solutions
of the linear program as saddle points of a modified Lagrangian function. We
show that the resulting continuous-time saddle-point algorithm is provably
correct but, in general, not distributed because of a global parameter
associated with the nonsmooth exact penalty function employed to encode the
inequality constraints of the linear program. This motivates the design of a
discontinuous saddle-point dynamics that, while enjoying the same convergence
guarantees, is fully distributed and scalable with the dimension of the
solution vector. We also characterize the robustness against disturbances and
link failures of the proposed dynamics. Specifically, we show that it is
integral-input-to-state stable but not input-to-state stable. The latter fact
is a consequence of a more general result, that we also establish, which states
that no algorithmic solution for linear programming is input-to-state stable
when uncertainty in the problem data affects the dynamics as a disturbance. Our
results allow us to establish the resilience of the proposed distributed
dynamics to disturbances of finite variation and recurrently disconnected
communication among the agents. Simulations in an optimal control application
illustrate the results
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
Feedback generation of quantum Fock states by discrete QND measures
A feedback scheme for preparation of photon number states in a microwave
cavity is proposed. Quantum Non Demolition (QND) measurement of the cavity
field provides information on its actual state. The control consists in
injecting into the cavity mode a microwave pulse adjusted to maximize the
population of the desired target photon number. In the ideal case (perfect
cavity and measures), we present the feedback scheme and its detailed
convergence proof through stochastic Lyapunov techniques based on
super-martingales and other probabilistic arguments. Quantum Monte-Carlo
simulations performed with experimental parameters illustrate convergence and
robustness of such feedback scheme.Comment: submitted, update version with feedback law of arXiv:0905.0114
[quant-ph
Review on computational methods for Lyapunov functions
Lyapunov functions are an essential tool in the stability analysis of dynamical systems, both in theory and applications. They provide sufficient conditions for the stability of equilibria or more general invariant sets, as well as for their basin of attraction. The necessity, i.e. the existence of Lyapunov functions, has been studied in converse theorems, however, they do not provide a general method to compute them. Because of their importance in stability analysis, numerous computational construction methods have been developed within the Engineering, Informatics, and Mathematics community. They cover different types of systems such as ordinary differential equations, switched systems, non-smooth systems, discrete-time systems etc., and employ di_erent methods such as series expansion, linear programming, linear matrix inequalities, collocation methods, algebraic methods, set-theoretic methods, and many others. This review brings these different methods together. First, the different types of systems, where Lyapunov functions are used, are briefly discussed. In the main part, the computational methods are presented, ordered by the type of method used to construct a Lyapunov function
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