Minimum norm regularization of descriptor systems by mixed output feedback

We study the regularization problem for linear, constant coefficient descriptor systems Ex' = Ax+Bu, y1 = Cx, y2 = Γx' by proportional and derivative mixed output feedback. Necessary and sufficient conditions are given, which guarantee that there exist output feedbacks such that the closed-loop system is regular, has index at most one and E+BGΓ has a desired rank, i.e., there is a desired number of differential and algebraic equations. To resolve the freedom in the choice of the feedback matrices we then discuss how to obtain the desired regularizing feedback of minimum norm and show that this approach leads to useful results in the sense of robustness only if the rank of E is decreased. Numerical procedures are derived to construct the desired feedback gains. These numerical procedures are based on orthogonal matrix transformations which can be implemented in a numerically stable way.

Feedback regulation by Atf3 in the endothelin-1-responsive transcriptome of cardiomyocytes: Egr1 is a principal Atf3 target

Endothelin-1 promotes cardiomyocyte hypertrophy by inducing changes in gene expression. Immediate early genes including activating transcription factor 3 (Atf3), Egr1 and Ptgs2 are rapidly and transiently upregulated by endothelin-1 in cardiomyocytes. Atf3 regulates expression of downstream genes and is implicated in negative feedback regulation of other immediate early genes. To identify Atf3-regulated genes, we knocked down Atf3 expression in cardiomyocytes exposed to endothelin-1 and used microarrays to interrogate the transcriptomic effects. Of upregulated mRNAs, expression of 23 (including Egr1, Ptgs2) was enhanced and expression of 25 was inhibited by Atf3 knockdown. Using quantitative PCR, we determined that knockdown of Atf3 had little effect on upregulation of Egr1 mRNA over 30 min, but abolished the subsequent decline, causing sustained Egr1 mRNA expression and enhanced protein expression. This resulted from direct binding of Atf3 to the Egr1 promoter. Mathematical modelling established that Atf3 can suffice to suppress Egr1 expression. Given the widespread co-regulation of Atf3 with Egr1, we suggest that the Atf3-Egr1 negative feedback loop is of general significance. Loss of Atf3 caused abnormal cardiomyocyte growth, presumably resulting from dysregulation of target genes. Our data therefore identify Atf3 as a nexus in cardiomyocyte hypertrophy required to facilitate the full and proper growth response.

Energy consumption feedback in perspective: integrating Australian data to meta-analyses on in home displays

Providing homeowners with real-time feedback on their electricity consumption through a dedicated display device has been shown to reduce consumption by approximately 6-10%. However, recent advances in smart grid technology have enabled larger sample sizes and more representative sample selection and recruitment methods for display trials. By analyzing these factors using data from current studies, this paper argues that a realistic, large-scale conservation effect from feedback is in the range of 3-5%. Subsequent analysis shows that providing real-time feedback may not be a cost effective strategy for reducing carbon emissions in Australia, but that it may enable additional benefits such as customer retention and peak-load shift.

The role of atmosphere feedbacks during ENSO in the CMIP3 models. Part III: the shortwave flux feedback

Previous studies using coupled general circulation models (GCMs) suggest that the atmosphere model plays a dominant role in the modeled El Nin ̃ o–Southern Oscillation (ENSO), and that intermodel differences in the thermodynamical damping of sea surface temperatures (SSTs) are a dominant contributor to the ENSO amplitude diversity. This study presents a detailed analysis of the shortwave flux feedback (aSW) in 12 Coupled Model Intercomparison Project phase 3 (CMIP3) simulations, motivated by findings that aSW is the primary contributor to model thermodynamical damping errors. A ‘‘feedback decomposition method,’’ developed to elucidate the aSW biases, shows that all models un- derestimate the dynamical atmospheric response to SSTs in the eastern equatorial Pacific, leading to un- derestimated aSW values. Biases in the cloud response to dynamics and the shortwave interception by clouds also contribute to errors in aSW. Changes in the aSW feedback between the coupled and corresponding atmosphere-only simulations are related to changes in the mean dynamics. A large nonlinearity is found in the observed and modeled SW flux feedback, hidden when linearly cal- culating aSW. In the observations, two physical mechanisms are proposed to explain this nonlinearity: 1) a weaker subsidence response to cold SST anomalies than the ascent response to warm SST anomalies and 2) a nonlinear high-level cloud cover response to SST. The shortwave flux feedback nonlinearity tends to be underestimated by the models, linked to an underestimated nonlinearity in the dynamical response to SST. The process-based methodology presented in this study may help to correct model ENSO atmospheric biases, ultimately leading to an improved simulation of ENSO in GCMs.