5,111 research outputs found
NLP Solutions as Asymptotic Values of ODE Trajectories
In this paper, it is shown that the solutions of general differentiable
constrained optimization problems can be viewed as asymptotic solutions to sets
of Ordinary Differential Equations (ODEs). The construction of the ODE
associated to the optimization problem is based on an exact penalty formulation
in which the weighting parameter dynamics is coordinated with that of the
decision variable so that there is no need to solve a sequence of optimization
problems, instead, a single ODE has to be solved using available efficient
methods. Examples are given in order to illustrate the results. This includes a
novel systematic approach to solve combinatoric optimization problems as well
as fast computation of a class of optimization problems using analogic circuits
leading to fast, parallel and highly scalable solutions
On Probabilistic Certification of Combined Cancer Therapies Using Strongly Uncertain Models
This paper proposes a general framework for probabilistic certification of
cancer therapies. The certification is defined in terms of two key issues which
are the tumor contraction and the lower admissible bound on the circulating
lymphocytes which is viewed as indicator of the patient health. The
certification is viewed as the ability to guarantee with a predefined high
probability the success of the therapy over a finite horizon despite of the
unavoidable high uncertainties affecting the dynamic model that is used to
compute the optimal scheduling of drugs injection. The certification paradigm
can be viewed as a tool for tuning the treatment parameters and protocols as
well as for getting a rational use of limited or expensive drugs. The proposed
framework is illustrated using the specific problem of combined
immunotherapy/chemotherapy of cancer.Comment: Submitted to Journal of theoretical Biolog
Stability proof for nonlinear MPC design using monotonically increasing weighting profiles without terminal constraints
In this note, a new formulation of Model Predictive Control (MPC) framework
with no stability-related terminal constraint is proposed and its stability is
proved under mild standard assumptions. The novelty in the formulation lies in
the use of time-varying monotonically increasing stage cost penalty. The main
result is that the -reachability prediction horizon can always be made
stabilizing provided that the increasing rate of the penalty is made
sufficiently high.Comment: Submitted to Automatic
Monitoring Control Updating Period In Fast Gradient Based NMPC
In this paper, a method is proposed for on-line monitoring of the control
updating period in fast-gradient-based Model Predictive Control (MPC) schemes.
Such schemes are currently under intense investigation as a way to accommodate
for real-time requirements when dealing with systems showing fast dynamics. The
method needs cheap computations that use the algorithm on-line behavior in
order to recover the optimal updating period in terms of cost function
decrease. A simple example of constrained triple integrator is used to
illustrate the proposed method and to assess its efficiency.Comment: 6 pages, 8 Figure
A New Contraction-Based NMPC Formulation Without Stability-Related terminal Constraints
Contraction-Based Nonlinear Model Predictive Control (NMPC) formulations are
attractive because of the generally short prediction horizons they require and
the needless use of terminal set computation that are commonly necessary to
guarantee stability. However, the inclusion of the contraction constraint in
the definition of the underlying optimization problem often leads to non
standard features such as the need for multi-step open-loop application of
control sequences or the use of multi-step memorization of the contraction
level that may induce unfeasibility in presence of unexpected disturbance. This
paper proposes a new formulation of contraction-based NMPC in which no
contraction constraint is explicitly involved. Convergence of the resulting
closed-loop behavior is proved under mild assumptions.Comment: accepted in short version IFAC Nolcos 2016. submitted to Automatica
as a technical communiqu
The effect of debt on corporate profitability : Evidence from French service sector
Current study aims to provide new empirical evidence on the impact of debt on
corporate profitability. This impact can be explained by three essential
theories: signaling theory, tax theory and the agency cost theory. Using panel
data sample of 2240 French non listed companies of service sector during
1999-2006. By utilizing generalized method of moments (GMM) econometric
technique on three measures of profitability ratio (PROF1, PROF2 and ROA), we
show that debt ratio has no effect on corporate profitability, regardless of
the size of company (VSEs, SMEs or LEs
On Adaptive Measurement Inclusion Rate In Real-Time Moving-Horizon Observers
This paper investigates a self adaptation mechanism regarding the rate with
which new measurements have to be incorporated in Moving-Horizon state
estimation algorithms. This investigation can be viewed as the dual of the one
proposed by the author in the context of real-time model predictive control. An
illustrative example is provided in order to assess the relevance of the
proposed updating rule.Comment: 6 pages. 4 Figure
- …