The main contribution of this paper is a procedure for the control by energy shaping of high-order port-Hamiltonian systems obtained from the spatial discretization of infinite dimensional dynamics. Beside the intrinsic difficulties related to the large number of state variables, the finite element model is generally given in terms of a Dirac structure and is completely a-causal, which implies ...

A nite element formulation to deal with the friction contact problem between an elastic body and a rigid foundation is presented. An augmented Lagrangian method, which incorporates two Lagrange multipliers and a slack variable in the constraint equation, is developed. In this method, the solution is achieved through a Newton-Raphson monolithic iterative strategy and leads to simple implementati...

Although block compressive sensing (BCS) makes it tractable to sense large-sized images and video, its recovery performance has yet to be significantly improved because its recovered images or video usually suffer from blurred edges, loss of details, and high-frequency oscillatory artifacts, especially at a low subrate. This paper addresses these problems by designing a modified total variation...

We consider the class of semi-infinite programming problems which became in recent years a powerful tool for the mathematical modelling of many real-life problems. In this paper, we study an augmented Lagrangian approach to semi-infinite problems and present necessary and sufficient conditions for the existence of corresponding augmented Lagrange multipliers. Furthermore, we discuss two particu...

The work presented here had excellent results on simple sites with few objectives. Unfortunately, when generalizing to complex cases with more objectives, the method of fast re­planning using Lagrangian multipliers behaved unpredictably. Not too bad, but also not good enough for clinical application. As such, this poster is useful to learn about what does not work.

The Gaussian vector multiple access channel with a sum-power constraint across all users, rather than the usual individual power constraint on each user, has recently been shown to be the dual of a Gaussian vector broadcast channel [1] [2]. Further, a numerical algorithm for the sum capacity under the sum power constraint has been proposed in [3]. This paper proposes a different algorithm for t...

We present a method for integrating the Progressive Hedging (PH) algorithm and the Dual Decomposition (DD) algorithm of Carøe and Schultz for stochastic mixed-integer programs. Based on the correspondence between lower bounds obtained with PH and DD, a method to transform weights from PH to Lagrange multipliers in DD is found. Fast progress in early iterations of PH speeds up convergence of DD ...

We revisit the problem of defining non-minimal gravity in the first order formalism. Specializing to scalar-tensor theories, which may be disguised as ‘higher-derivative’ models with the gravitational Lagrangians that depend only on the Ricci scalar, we show how to recast these theories as Palatini-like gravities. The correct formulation utilizes the Lagrange multiplier method, which preserves ...

A large class of optimization problems can be modeled as minimization of an objective function subject to constraints given in a form of set inclusions. We discuss in this paper augmented Lagrangian duality for such optimization problems. We formulate the augmented Lagrangian dual problems and study conditions ensuring existence of the corresponding augmented Lagrange multipliers. We also discu...

Augmented Lagrangian methods are effective tools for solving large-scale nonlinear programming problems. At each outer iteration a minimization subproblem with simple constraints, whose objective function depends on updated Lagrange multipliers and penalty parameters, is approximately solved. When the penalty parameter becomes very large the subproblem is difficult, therefore the effectiveness ...