Maximum Likelihood Estimation of the Parameters of Linear Systems

A method is presented which estimates the parameters of Linear Systems (LS), modelled by their transfer function, using a very efficient iteration algorithm. The estimator is an error in variables method and takes into account the noise on the input and output measurements. During the estimation process, an approximation of the Cramer-Rao lower bound on the covariance matrix of the estimates is derived and the 'mean' model error is discussed

Identification of the accretion rate for annually resolved archives

International audienceThe past environment is often reconstructed by measuring a given proxy (e.g. ?18O) in an environmental archive, i.e. a species which gradually accumulates mass and records the current environment during this mass formation (e.g. corals, shells, trees, etc...). When such an environmental proxy is measured, its values are known as a function of distance. However, to relate the data to environmental variations, the date associated with each measurement, i.e. the time base, should be known. This is not straightforward solved, since species usually do not grow at constant rates. In this paper, we investigate this problem for annually resolved archives, which exhibit a certain periodicity. Such signals are often found in clams or corals. Due to variations in accretion rate the data along the distance axis have a disturbed periodic profile. A method is developed to extract information about the accretion rate, such that the original (periodic) signal as function of time can be recovered. Simultaneously the exact shape of the periodic signal is estimated. The final methodology is quasi-independent of choices made by the investigator. Every step in the procedure is described in detail and finally, the method is exemplified on a real world example

Timing and placing samplings to optimally calibrate a reactive transport model: exploring the potential for <i>Escherichia coli</i> in the Scheldt estuary

For the calibration of any model, measurements are necessary. As measurements are expensive, it is of interest to determine beforehand which kind of samples will provide the maximum of information. Using a criterion related to the Fisher information matrix, it is possible to design a sampling scheme that will enable the most precise model parameter estimates. This approach was applied to a reactive transport model (based on SLIM) of Escherichia coli in the Scheldt Estuary. As this estuary is highly influenced by the tide, it is expected that careful timing of the samples with respect to the tidal cycle will have an effect on the quality of the data. The timing and also the positioning of samples were optimised according to the proposed criterion. In the investigated case studies the precision of the estimated parameters could be improved by up to a factor of ten, confirming the usefulness of this approach to maximize the amount of information that can be retrieved from a fixed number of samples

Resilient Parameter-Invariant Control With Application to Vehicle Cruise Control

This work addresses the general problem of resilient control of unknown stochastic linear time-invariant (LTI) systems in the presence of sensor attacks. Motivated by a vehicle cruise control application, this work considers a first order system with multiple measurements, of which a bounded subset may be corrupted. A frequency-domain-designed resilient parameter-invariant controller is introduced that simultaneously minimizes the effect of corrupted sensors, while maintaining a desired closed-loop performance, invariant to unknown model parameters. Simulated results illustrate that the resilient parameter-invariant controller is capable of stabilizing unknown state disturbances and can perform state trajectory tracking

Frequency-domain subspace identification of nonlinear mechanical systems - Application to a solar array structure

The present paper addresses the experimental identification of a simplified realisation of a solar array structure in folded configuration. To this end, a nonlinear subspace identification technique formulated in the frequency domain, referred to as the FNSI method, is exploited. The frequency response functions of the underlying linear structure and the nonlinear coefficients are estimated by this approach. Nonlinearity is caused by impacts between adjacent panels and friction and gaps appearing in their clamping interfaces. This application is challenging for several reasons, which include high modal density and the complicated nature of the involved nonlinear mechanisms

Differential effects of high fat diet-induced obesity on oocyte mitochondrial functions in inbred and outbred mice

Maternal obesity can cause reduced oocyte quality and subfertility. Mitochondrial dysfunction plays a central role here, and most often inbred mouse models are used to study these pathways. We hypothesized that the mouse genetic background can influence the impact of high fat diet (HFD)-induced obesity on oocyte quality. We compared the inbred C57BL/6 (B6) and the outbred Swiss strains after feeding a HFD for 13w. HFD-mice had increased body weight gain, hypercholesterolemia, and increased oocyte lipid droplet (LD) accumulation in both strains. LD distribution was strain-dependent. In Swiss mouse oocytes, HFD significantly increased mitochondrial inner membrane potential (MMP), reactive oxygen species concentrations, mitochondrial ultrastructural abnormalities (by 46.4%), and endoplasmic reticulum (ER) swelling, and decreased mtDNA copy numbers compared with Swiss controls (P0.1). Interestingly, mtDNA in B6-HFD oocytes was increased suggesting defective mitophagy. In conclusion, we show evidence that the genetic background or inbreeding can affect mitochondrial functions in oocytes and may influence the impact of HFD on oocyte quality. These results should create awareness when choosing and interpreting data obtained from different mouse models before extrapolating to human applications

Identification of single-input–single-output quantum linear systems

The purpose of this paper is to investigate system identification for single-input–single-output general (active or passive) quantum linear systems. For a given input we address the following questions: (1) Which parameters can be identified by measuring the output? (2) How can we construct a system realization from sufficient input-output data? We show that for time-dependent inputs, the systems which cannot be distinguished are related by symplectic transformations acting on the space of system modes. This complements a previous result of Guţă and Yamamoto [IEEE Trans. Autom. Control 61, 921 (2016)] for passive linear systems. In the regime of stationary quantum noise input, the output is completely determined by the power spectrum. We define the notion of global minimality for a given power spectrum, and characterize globally minimal systems as those with a fully mixed stationary state. We show that in the case of systems with a cascade realization, the power spectrum completely fixes the transfer function, so the system can be identified up to a symplectic transformation. We give a method for constructing a globally minimal subsystem direct from the power spectrum. Restricting to passive systems the analysis simplifies so that identifiability may be completely understood from the eigenvalues of a particular system matrix

Intermittent control models of human standing: similarities and differences

Two architectures of intermittent control are compared and contrasted in the context of the single inverted pendulum model often used for describing standing in humans. The architectures are similar insofar as they use periods of open-loop control punctuated by switching events when crossing a switching surface to keep the system state trajectories close to trajectories leading to equilibrium. The architectures differ in two significant ways. Firstly, in one case, the open-loop control trajectory is generated by a system-matched hold, and in the other case, the open-loop control signal is zero. Secondly, prediction is used in one case but not the other. The former difference is examined in this paper. The zero control alternative leads to periodic oscillations associated with limit cycles; whereas the system-matched control alternative gives trajectories (including homoclinic orbits) which contain the equilibrium point and do not have oscillatory behaviour. Despite this difference in behaviour, it is further shown that behaviour can appear similar when either the system is perturbed by additive noise or the system-matched trajectory generation is perturbed. The purpose of the research is to come to a common approach for understanding the theoretical properties of the two alternatives with the twin aims of choosing which provides the best explanation of current experimental data (which may not, by itself, distinguish beween the two alternatives) and suggesting future experiments to distinguish between the two alternatives