Search results for "system identification"
showing 10 items of 56 documents
Hammerstein Model-Based Robust Control of DC/DC Converters
2007
This paper deals with model-based robust control of DC/DC power electronic converters. The converter is modelled by means of its static characteristic and a few continuous-time linear and time-invariant (LTI) models corresponding to contiguous ranges of duty-cycle. The model appears as a Hammerstein model in which the values of the parameters of the LTI part depend on the actual duty-cycle operating range. This suggests to describe the converter as an uncertain system to be controlled using robust control techniques. Frequency domain approach is used for describing the nominal model and the uncertainty. In view of applying robust control, identification of the LTI models is performed by mea…
LPV Model Identification For The Stall And Surge Control of a Jet Engine
2001
Abstract The problem of identifying discrete-time Linear Parameter Varying (LPV) models of non-linear or time-varying systems for gain scheduling control is considered assuming that inputs, outputs and the scheduling parameters are measured, and a form of the functional dependence of the coefficients on the parameters is known. The identification procedure is applied to the controlled model of compressors for jet engines. The model is controlled in order to avoid rotating stall and surge. Aim of the present paper is to identify the LPV model based on the nonlinear model of compressors in order to design a robust gain scheduling predictive controller.
A framework for assessing frequency domain causality in physiological time series with instantaneous effects.
2013
We present an approach for the quantification of directional relations in multiple time series exhibiting significant zero-lag interactions. To overcome the limitations of the traditional multivariate autoregressive (MVAR) modelling of multiple series, we introduce an extended MVAR (eMVAR) framework allowing either exclusive consideration of time-lagged effects according to the classic notion of Granger causality, or consideration of combined instantaneous and lagged effects according to an extended causality definition. The spectral representation of the eMVAR model is exploited to derive novel frequency domain causality measures that generalize to the case of instantaneous effects the kno…
Simulation and Parameter-Identification of the Closed-Loop Cardiovascular System by the Use of a Nonlinear Mathematical Model
1981
Abstract A non-linear model of human cardio-vascular system, which includes the short-term pressure regulation mechanism was mathematically derived and implemented on a PDP-11/45 in a block-oriented, interactive programming language. In this way the behaviour of the arterial and venous pressures, cardiac output, stroke volume, total peripheral resistance and heart-rate under ergometric workload was studied by simulation, and experimentally proved, that the model matches the system with good accuracy. In a second phase the parameters of the model were identified by the use of the output-error method. For this purpose a non-linear system identification programming package was applied. The par…
Identification and validation of quasispecies models for biological systems
2009
An identification procedure for biological systems cast as quasi-species models is proposed. Their identification is a challenging problem because of the bilinear dependence on the parameters and their physical constraints. The proposed solution is within the framework of set-membership identification. %The bilinear dependence on parameters of the model and their physical constraints make the present issue challenging. We determine an estimate of the model parameters together with their interval of variability (Uncertainty Intervals), taking into account all the physical constraints. Invalidation/validation is performed on the basis of the predictive capability of the estimated models. The …
Model Identification of a Network as Compressing Sensing
2013
In many applications, it is important to derive information about the topology and the internal connections of dynamical systems interacting together. Examples can be found in fields as diverse as Economics, Neuroscience and Biochemistry. The paper deals with the problem of deriving a descriptive model of a network, collecting the node outputs as time series with no use of a priori insight on the topology, and unveiling an unknown structure as the estimate of a "sparse Wiener filter". A geometric interpretation of the problem in a pre-Hilbert space for wide-sense stochastic processes is provided. We cast the problem as the optimization of a cost function where a set of parameters are used t…
Optimal measurement setup for damage detection in piezoelectric plates
2009
[EN] An optimization of the excitation-measurement configuration is proposed for the characterization of damage in PZT-4 piezoelectric plates, from a numerical point of view. To perform such an optimization, a numerical method to determine the location and extent of defects in piezoelectric plates is developed by combining the solution of an identification inverse problem, using genetic algorithms and gradient-based methods to minimize a cost functional, and using an optimized finite element code and meshing algorithm. In addition, a semianalytical estimate of the probability of detection is developed and validated, which provides a flexible criterion to optimize the experimental design. Th…
A new dynamic identification technique: application to the evaluation of the equivalent strut for infilled frames
2003
A new time domain identification technique for systems under Gaussian white noise input is presented, requiring for its application the measurement of the system response but no information about input intensity. The technique proposed is based on the statistic moment equations derived by using a special class of mathematical models named "potential models". These models allow one to determine fundamental properties of the response statistics, making it possible to identify stiffness and dissipation features of a structural system, and also to determine the excitation input. The technique proposed is here applied to the identification of the strut equivalent to the infill of a single story-…
Approximation of the Feasible Parameter Set in worst-case identification of Hammerstein models
2005
The estimation of the Feasible Parameter Set (FPS) for Hammerstein models in a worst-case setting is considered. A bounding procedure is determined both for polytopic and ellipsoidic uncertainties. It consists in the projection of the FPS of the extended parameter vector onto suitable subspaces and in the solution of convex optimization problems which provide Uncertainties Intervals of the model parameters. The bounds obtained are tighter than in the previous approaches. hes.
Robust estimation of partial directed coherence by the vector optimal parameter search algorithm
2009
We propose a method for the accurate estimation of Partial Directed Coherence (PDC) from multichannel time series. The method is based on multivariate vector autoregressive (MVAR) model identification performed through the recently proposed Vector Optimal Parameter Search (VOPS) algorithm. Using Monte Carlo simulations generated by different MVAR models, the proposed VOPS algorithm is compared with the traditional Vector Least Squares (VLS) identification method. We show that the VOPS provides more accurate PDC estimates than the VLS (either overall and single-arc errors) in presence of interactions with long delays and missing terms, and for noisy multichannel time series. ©2009 IEEE.