11,277 research outputs found
The Libyan civil conflict : selected case series of orthopaedic trauma managed in Malta in 2014
Aim: The purpose of this series of cases was to analyse our management of orthopaedic trauma casualties in the
Libyan civil war crisis in the European summer of 2014. We looked at both damage control orthopaedics and for
case variety of war trauma at a civilian hospital. Due to our geographical proximity to Libya, Malta was the closest
European tertiary referral centre. Having only one Level 1 trauma care hospital in our country, our Trauma and
Orthopaedics department played a pivotal role in the management of Libyan battlefield injuries. Our aims were to
assess acute outcomes and short term mortality of surgery within the perspective of a damage control orthopaedic
strategy whereby aggressive wound management, early fixation using relative stability principles, antibiotic cover
with adequate soft tissue cover are paramount. We also aim to describe the variety of war injuries we came across,
with a goal for future improvement in regards to service providing.Methods: Prospective collection of six interesting cases with severe limb and spinal injuries sustained in Libya
during the Libyan civil war between June and November 2014.Conclusions: We applied current trends in the treatment of war injuries, specifically in damage control orthopaedic
strategy and converting to definitive treatment where permissible. The majority of our cases were classified as most
severe (Type IIIB/C) according to the Gustilo-Anderson classification of open fractures. The injuries treated reflected
the type of standard and improved weaponry available in modern warfare affecting both militants and civilians
alike with increasing severity and extent of damage. Due to this fact, multidisciplinary team approach to patient
centred care was utilised with an ultimate aim of swift recovery and early mobilisation. It also highlighted the
difficulties and complex issues required on a hospital management level as a neighbouring country to war zone
countries in transforming care of civil trauma to military trauma.peer-reviewe
Stability and Performance Verification of Optimization-based Controllers
This paper presents a method to verify closed-loop properties of
optimization-based controllers for deterministic and stochastic constrained
polynomial discrete-time dynamical systems. The closed-loop properties amenable
to the proposed technique include global and local stability, performance with
respect to a given cost function (both in a deterministic and stochastic
setting) and the gain. The method applies to a wide range of
practical control problems: For instance, a dynamical controller (e.g., a PID)
plus input saturation, model predictive control with state estimation, inexact
model and soft constraints, or a general optimization-based controller where
the underlying problem is solved with a fixed number of iterations of a
first-order method are all amenable to the proposed approach.
The approach is based on the observation that the control input generated by
an optimization-based controller satisfies the associated Karush-Kuhn-Tucker
(KKT) conditions which, provided all data is polynomial, are a system of
polynomial equalities and inequalities. The closed-loop properties can then be
analyzed using sum-of-squares (SOS) programming
Quantization Design for Distributed Optimization
We consider the problem of solving a distributed optimization problem using a
distributed computing platform, where the communication in the network is
limited: each node can only communicate with its neighbours and the channel has
a limited data-rate. A common technique to address the latter limitation is to
apply quantization to the exchanged information. We propose two distributed
optimization algorithms with an iteratively refining quantization design based
on the inexact proximal gradient method and its accelerated variant. We show
that if the parameters of the quantizers, i.e. the number of bits and the
initial quantization intervals, satisfy certain conditions, then the
quantization error is bounded by a linearly decreasing function and the
convergence of the distributed algorithms is guaranteed. Furthermore, we prove
that after imposing the quantization scheme, the distributed algorithms still
exhibit a linear convergence rate, and show complexity upper-bounds on the
number of iterations to achieve a given accuracy. Finally, we demonstrate the
performance of the proposed algorithms and the theoretical findings for solving
a distributed optimal control problem
A Parametric Non-Convex Decomposition Algorithm for Real-Time and Distributed NMPC
A novel decomposition scheme to solve parametric non-convex programs as they
arise in Nonlinear Model Predictive Control (NMPC) is presented. It consists of
a fixed number of alternating proximal gradient steps and a dual update per
time step. Hence, the proposed approach is attractive in a real-time
distributed context. Assuming that the Nonlinear Program (NLP) is
semi-algebraic and that its critical points are strongly regular, contraction
of the sequence of primal-dual iterates is proven, implying stability of the
sub-optimality error, under some mild assumptions. Moreover, it is shown that
the performance of the optimality-tracking scheme can be enhanced via a
continuation technique. The efficacy of the proposed decomposition method is
demonstrated by solving a centralised NMPC problem to control a DC motor and a
distributed NMPC program for collaborative tracking of unicycles, both within a
real-time framework. Furthermore, an analysis of the sub-optimality error as a
function of the sampling period is proposed given a fixed computational power.Comment: 16 pages, 9 figure
An Alternating Trust Region Algorithm for Distributed Linearly Constrained Nonlinear Programs, Application to the AC Optimal Power Flow
A novel trust region method for solving linearly constrained nonlinear
programs is presented. The proposed technique is amenable to a distributed
implementation, as its salient ingredient is an alternating projected gradient
sweep in place of the Cauchy point computation. It is proven that the algorithm
yields a sequence that globally converges to a critical point. As a result of
some changes to the standard trust region method, namely a proximal
regularisation of the trust region subproblem, it is shown that the local
convergence rate is linear with an arbitrarily small ratio. Thus, convergence
is locally almost superlinear, under standard regularity assumptions. The
proposed method is successfully applied to compute local solutions to
alternating current optimal power flow problems in transmission and
distribution networks. Moreover, the new mechanism for computing a Cauchy point
compares favourably against the standard projected search as for its activity
detection properties
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