In this brief, constrained multi variable model predictive control (MPC) strategy is investigated for a GE9001E gas turbine power plant. So the rotor speed and exhaust gas temperature are controlled manipulating the fuel command and compressor inlet guide vanes position. A nonlinear model is introduced using conventional mathematical models and ARX identification procedure as gas turbine plant ...

BACKGROUND Aristaless related homeobox (ARX) is a paired-type homeobox gene. ARX function is frequently affected by naturally occurring mutations. Nonsense mutations, polyalanine tract expansions and missense mutations in ARX cause a range of intellectual disability and epilepsy phenotypes with or without additional features including hand dystonia, lissencephaly, autism or dysarthria. Severe m...

Industrial process control systems commonly exhibit features of time-varying behavior, strong coupling, and nonlinearity. Obtaining accurate mathematical models these nonlinear achieving satisfactory performance is still a challenging task. In this paper, data-driven modeling techniques deep learning methods are used to accurately capture category smooth system’s spatiotemporal features. The op...

The Arx transcription factor is expressed in the developing ventral telencephalon and subsets of its derivatives. Mutation of human ARX ortholog causes neurological disorders including epilepsy, lissencephaly, and mental retardation. We have isolated the mouse Arx endogenous enhancer modules that control its tightly compartmentalized forebrain expression. Interestingly, they are scattered downs...

ARX (the aristaless-related homeobox gene) is a transcription factor that participates in the development of GABAergic and cholinergic neurons in the forebrain. Many ARX mutations have been identified in X-linked lissencephaly and mental retardation with epilepsy, and thus ARX is considered to be a causal gene for the two syndromes although the neurobiological functions of each mutation remain ...

The human controller (HC) can greatly improve target-tracking performance by utilizing a feedforward operation on the target signal, in addition to a feedback response. System identification methods are used to determine the correct HC model structure: purely feedback or a combined feedforward/feedback model. In this paper, we investigate three central issues that complicate this objective. Fir...

Identification of autoregressive models with exogenous input (ARX) is a classical problem in system identification. This article considers the errors-in-variables (EIV) ARX model identification problem, where measurements are also corrupted noise. The recently proposed Dynamic Iterative Principal Components Analysis (DIPCA) technique solves EIV but only applicable to white measurement errors. W...

Intestinal hormones are key regulators of digestion and energy homeostasis secreted by rare enteroendocrine cells. These cells produce over ten different hormones including GLP-1 and GIP peptides known to promote insulin secretion. To date, the molecular mechanisms controlling the specification of the various enteroendocrine subtypes from multipotent Neurog3(+) endocrine progenitor cells, as we...

We propose a method to estimate the glottal flow based on the ARX model of speech production and on the LF model of glottal flow. This method splits the analysis in two stages: a low frequency analysis to estimate the glottal source parameters which have mainly a low pass effect and a second step to refine the parameters which have also a high pass effect. Along with this new analysis scheme, w...

In this paper, we consider identifying Auto Regressive with eXternal input (ARX) models for both Linear Time-Invariant (LTI) and Linear Time-Variant (LTV) systems. We aim at doing the identification from the smallest possible number of observations. This is inspired by the field of Compressive Sensing (CS), and for this reason, we call this problem Compressive System Identification (CSI). In th...