Publicaties
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Online automatic identification of modal parameters of a bridge using the p-LSCF method KU Leuven
A concrete arch bridge over the Douro River, at the City of Porto in Portugal, is being monitored by twelve accelerometers since September 2007. The present paper describes in detail the methodology used to perform the on-line automatic identification of the modal parameters using the poly-Least Squares Complex Frequency Domain method (p-LSCF). The results obtained with this algorithm are compared with the ones obtained with the previously ...
Parameter identification of Droop model: an experimental case study KU Leuven
Mathematical modeling and the development of predictive dynamic models are of paramount importance for the optimization, state estimation, and control of bioprocesses. This study is dedicated to the identification of a simple model of microalgae growth under substrate limitation, i.e., Droop model, and describes the design and instrumentation of a lab-scale flat-plate photobioreactor, the associated on-line and off-line instrumentation, the ...
Numerical estimation and experimental verification of optimal parameter identification based on modern optimization of a three phase induction motor Universiteit Gent
The parameters of electric machines play a substantial role in the control system which, in turn, has a great impact on machine performance. In this paper, a proposed optimal estimation method for the electrical parameters of induction motors is presented. The proposed method uses the particle swarm optimization (PSO) technique. Further, it also considers the influence of temperature on the stator resistance. A complete experimental setup was ...
Online identification of a two-mass system in frequency domain using a Kalman filter Universiteit Antwerpen Universiteit Gent
Some of the most widely recognized online parameter estimation techniques used in different servomechanism are the extended Kalman filter (EKF) and recursive least squares (RLS) methods. Without loss of generality, these methods are based on a prior knowledge of the model structure of the system to be identified, and thus, they can be regarded as parametric identification methods. This paper proposes an on-line non-parametric frequency response ...
Online identification of a mechanical system in frequency domain using sliding DFT Universiteit Antwerpen
A proper real-time system identification method is of great importance in order to acquire an analytical model that sufficiently represents the characteristics of the monitored system. While the use of different time-domain online identification techniques has been widely recognized as a powerful approach to system diagnostics, the frequency-domain identification techniques have primarily been considered for offline commissioning purposes. This ...
Online identification of electrically stimulated muscle models. Vrije Universiteit Brussel
Online identification of electrically stimulated muscle under isometric conditions, modeled as a Hammerstein structure, is investigated in this paper. Motivated by the significant time-varying properties of muscle, a novel recursive algorithm for Hammerstein structure is developed. The linear and nonlinear parameters are separated and estimated recursively in a parallel manner, with each updating algorithm using the most up-to-date estimation ...
An Online Framework for State of Charge Determination of Battery Systems using Combined System Identification Approach Vrije Universiteit Brussel
State of Charge (SoC) of a battery is a measure of the amount of electrical energy stored in the battery. The prerequisite for state of charge determination in Electrical Vehicle (EV) and stationary batteries is more challenging as the battery can be composed of hundreds of cells while load current changes dramatically inside the cells and required elapsed time for SoC determination should be as short as possible for battery pack management to ...
Parameter estimation for a ship's roll response model in shallow water using an intelligent machine learning method Universiteit Gent Waterbouwkundig Laboratorium
In order to accurately identify the ship's roll model parameters in shallow water, and solve the problems of difficult estimating nonlinear damping coefficients by traditional methods, a novel Nonlinear Least Squares Support Vector Machine (NLS-SVM) is introduced. To illustrate the validity and applicability of the proposed method, simulation and decay tests data are combined and utilized to estimate unknown parameters and predict the roll ...
Split-Horizon Scheme for On-line Friction Parameter Estimation KU Leuven
Friction model identification is in most cases carried out in an off-line manner, where separate measurements are performed to identify the presliding and sliding friction characteristics using specific excitation signals. This work presents some preliminary results of a slip horizon estimator where friction parameters are updated on-line during regular point-to-point motions.