Search results for "Parameter identification"
showing 10 items of 30 documents
Parameter identification of induction motor model by means of State Space-Vector Model Output Error Minimization
2014
This paper proposes a technique for the off-line estimation of the electrical parameters of the equivalent circuit of an Induction Machines (IM), and focuses on the application of an algorithm based on the minimization of a suitable cost function involving the differences between the measured stator current direct (sD) and quadrature (sQ) components and the corresponding estimated by the IM state model. This method exploits an entire start-up transient of the IM to estimate all of the 4 electrical parameters of the machine (Rs, Ls, σLs, Tr). It proposes also a set of tests to be made in order to estimate the variation of the magnetic parameters of the IM versus the rotor magnetizing current…
A Sequential Quadratic Programming Method for Volatility Estimation in Option Pricing
2006
Our goal is to identify the volatility function in Dupire's equation from given option prices. Following an optimal control approach in a Lagrangian framework, we propose a globalized sequential quadratic programming (SQP) algorithm with a modified Hessian - to ensure that every SQP step is a descent direction - and implement a line search strategy. In each level of the SQP method a linear-quadratic optimal control problem with box constraints is solved by a primal-dual active set strategy. This guarantees L^1 constraints for the volatility, in particular assuring its positivity. The proposed algorithm is founded on a thorough first- and second-order optimality analysis. We prove the existe…
NOVEL TOOLS FOR THE MECHANICAL ANALYSIS OF THIN PLATES AND RELEVANCE ON MEMBRANE-BASED TECHNOLOGIES
2020
Analysis of Rectangular Orthotropic Membranes for Mechanical Properties Identification through Load-Displacement Data
2021
In this paper, an innovative procedure is introduced for the identification of the mechanical properties of orthotropic membranes based on load-displacement data. To this end, novel functional forms of the displacement components for rectangular membranes are appropriately introduced. Unknown coefficients of these displacement functions are determined, minimizing the total potential energy of the membrane. The energy method is then combined with an optimization procedure to estimate the elastic constants of the membranes in a straightforward manner. Specifically, a genetic algorithm is used to minimize a properly defined objective function directly related to the sought mechanical propertie…
Identification of linear parameter varying models
2002
We consider identification of a certain class of discrete-time nonlinear systems known as linear parameter varying system. We assume that inputs, outputs and the scheduling parameters are directly measured, and a form of the functional dependence of the system coefficients on the parameters is known. We show how this identification problem can be reduced to a linear regression, and provide compact formulae for the corresponding least mean square and recursive least-squares algorithms. We derive conditions on persistency of excitation in terms of the inputs and scheduling parameter trajectories when the functional dependence is of polynomial type. These conditions have a natural polynomial i…
The Hu-Washizu variational principle for the identification of imperfections in beams
2008
This paper presents a procedure for the identification of imperfections of structural parameters based on displacement measurements by static tests. The proposed procedure is based on the well-known Hu–Washizu variational principle, suitably modified to account for the response measurements, which is able to provide closed-form solutions to some inverse problems for the identification of structural parameter imperfections in beams. Copyright © 2008 John Wiley & Sons, Ltd.
A Numerical Method for an Inverse Problem Arising in Two-Phase Fluid Flow Transport Through a Homogeneous Porous Medium
2019
In this paper we study the inverse problem arising in the model describing the transport of two-phase flow in porous media. We consider some physical assumptions so that the mathematical model (direct problem) is an initial boundary value problem for a parabolic degenerate equation. In the inverse problem we want to determine the coefficients (flux and diffusion functions) of the equation from a set of experimental data for the recovery response. We formulate the inverse problem as a minimization of a suitable cost function and we derive its numerical gradient by means of the sensitivity equation method. We start with the discrete formulation and, assuming that the direct problem is discret…
A linear approach for the nonlinear distributed parameter identification problem
1991
In identifying the nonlinear distributed parameters we propose an approach, which enables us to identify the nonlinear distributed parameters by just solving linear problems. In this approach we just need to identify linear parameters and then recover the nonlinear parameters from the identified linear parameters. An error estimate for the finite element approximation is derived. Numerical tests are also presented.
Identification for a general class of LPV Models
2000
Abstract In this paper we consider the problem of identifying discrete-time Linear Parameter Varying (LPV) models of non-linear or time-varying systems. LPV models are considered for their connection with the industrial practice of gain-scheduling. We assume that inputs, outputs and the scheduling parameters are measured, and a form of the functional dependence of the coefficients on the parameters is known. We show how the identification problem can be reduced to a linear regression so that a Least Mean Square identification algorithm can be reformulated. Conditions on the persistency of excitation in terms of the inputs and parameter trajectories are given to ensure the consistency of the…
Identification of linear parameter varying models
2003
We consider the problem of identifying discrete-time linear parameter varying models of nonlinear or time-varying systems. We assume that inputs, outputs and the scheduling parameters are measured, and a form of the functional dependence of the coefficients on the parameters. We show how the identification problem can be reduced to a linear regression, and we give conditions on persistency of excitation in terms of the inputs and parameter trajectories.