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3 results on '"Hof, Paul M. J. Van den"'

1. A Local Direct Method for Module Identification in Dynamic Networks With Correlated Noise.

Author

Ramaswamy, Karthik Raghavan and Hof, Paul M. J. Van den

Subjects
*NOISE, *CONFOUNDING variables, *PARAMETER identification, *MISO
Abstract

The identification of local modules in dynamic networks with known topology has recently been addressed by formulating conditions for arriving at consistent estimates of the module dynamics, under the assumption of having disturbances that are uncorrelated over the different nodes. The conditions typically reflect the selection of a set of node signals that are taken as predictor inputs in an multiple-input-single-output (MISO) identification setup. In this paper an extension is made to arrive at an identification setup for the situation that process noises on the different node signals can be correlated with each other. In this situation the local module may need to be embedded in an multiple-input--multiple-output (MIMO) identification setup for arriving at a consistent estimate with maximum likelihood properties. This requires the proper treatment of confounding variables. The result is a set of algorithms that, based on the given network topology and disturbance correlation structure, selects an appropriate set of node signals as predictor inputs and outputs in an MISO or MIMO identification setup. Three algorithms are presented that differ in their approach of selecting measured node signals. Either a maximum or a minimum number of measured node signals can be considered, as well as a preselected set of measured nodes. [ABSTRACT FROM AUTHOR]

Published
2021
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2. Active Deformation Control for a Magnetically Levitated Planar Motor Mover.

Author

Proimadis, Ioannis, Custers, Coen H. H. M., Toth, Roland, Jansen, J. W., Butler, Hans, Lomonova, Elena, and Hof, Paul M. J. Van den

Subjects
*PERMANENT magnets, *DEFORMATIONS (Mechanics), *PERMANENT magnet motors, *SUPERCONDUCTING magnets, *MOTORS, *STORAGE & moving industry
Abstract

This article describes a method for the active control of the deformations on a magnetically levitated moving-magnet planar motor. The planar motor under consideration is comprised of a stator on a double coil array configuration and a mover with permanent magnets, and it is designed to perform positioning tasks with nanometer level of accuracy. Due to the spatially asymmetric, nonuniform force distribution on the magnet plate, mechanical deformations are induced to the mover, which can severely hinder the desired positioning accuracy. The proposed method overcomes this challenge by properly shaping the force distribution on the moving magnet plate, which is enabled by the presence of multiple coils interacting with the mover, corresponding to an “overactuation” scheme. As a consequence, the independent control of elementary deformation shapes (modes) is achieved. The proposed overactuation scheme is experimentally validated on a planar motor prototype, proving the efficiency of the proposed method during both standstill and motion. [ABSTRACT FROM AUTHOR]

Published
2022
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3. Estimating parameters with pre-specified accuracies in distributed parameter systems using optimal experiment design.

Author

Potters, M. G., Bombois, X., Mansoori, M., and Hof, Paul M. J. Van den

Subjects
*HEAT transfer, *THERMAL conductivity, *ACTUATORS, *PARAMETER estimation, *PARTIAL differential equations, *ALGORITHMS
Abstract

Estimation of physical parameters in dynamical systems driven by linear partial differential equations is an important problem. In this paper, we introduce the least costly experiment design framework for these systems. It enables parameter estimation with an accuracy that is specified by the experimenter prior to the identification experiment, while at the same time minimising the cost of the experiment. We show how to adapt the classical framework for these systems and take into account scaling and stability issues. We also introduce a progressive subdivision algorithm that further generalises the experiment design framework in the sense that it returns the lowest cost by finding the optimal input signal, and optimal sensor and actuator locations. Our methodology is then applied to a relevant problem in heat transfer studies: estimation of conductivity and diffusivity parameters in front-face experiments. We find good correspondence between numerical and theoretical results. [ABSTRACT FROM AUTHOR]

Published
2016
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