Purpose - The purpose of this paper is to present the solution of a highly nonlinear fluid dynamics in a low Prandtl number regime, typical for metal-like materials, as defined in the call for contributions to a numer...
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Set-based estimation for nonlinear systems is a useful tool to handle sparse and uncertain data. The tool provides outer bounds on feasible parameter sets and reachable states, as well as provable inconsistency certif...
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ISBN:
(纸本)9781479901890
Set-based estimation for nonlinear systems is a useful tool to handle sparse and uncertain data. The tool provides outer bounds on feasible parameter sets and reachable states, as well as provable inconsistency certificates for entire parameter regions. In case of errors in the data such as outliers or incorrect a priori assumptions on variable uncertainties, set-based approaches can, however, lead to poor estimates or even rejection of a consistent model. We present a set-based approach to systematically identify outliers or incorrect variable uncertainty assumptions. The basic idea is to detect outliers by quantifying the influence they have on the inconsistency of an underlying feasibility problem. The results build on a set-based estimation framework that employs convex relaxations. Specifically we derive model consistency measures and sensitivity measures that combine the sensitivity information stored in the Lagrange dual variables. An algorithm is developed that iteratively detects outliers that contribute most to inconsistency. The algorithm terminates once the data and model are no longer proved inconsistent. The approach is illustrated by an example.
Effective fault diagnosis depends on the detectability of the faults in the measurements, which can be improved by a suitable input signal. This article presents a deterministic method for computing the set of inputs ...
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ISBN:
(纸本)9781479901777
Effective fault diagnosis depends on the detectability of the faults in the measurements, which can be improved by a suitable input signal. This article presents a deterministic method for computing the set of inputs that guarantee fault diagnosis, referred to as separating inputs. The process of interest is described, under nominal and various faulty conditions, by linear discrete-time models subject to bounded process and measurement noise. It is shown that the set of separating inputs can be efficiently computed in terms of the complement of one or several zonotopes, depending on the number of fault models. In practice, it is essential to choose elements from this set that are minimally harmful with respect to other control objectives. It is shown that this can be done efficiently through the solution of a mixed-integer quadratic program. The method is demonstrated for a numerical example.
In this work we focus on unique diagnosability of parametric faults in the presence of measurement uncertainty and model mismatches. Specifically, we formulate a condition for diagnosability of parametric faults in a ...
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ISBN:
(纸本)9781467357159
In this work we focus on unique diagnosability of parametric faults in the presence of measurement uncertainty and model mismatches. Specifically, we formulate a condition for diagnosability of parametric faults in a set-based framework that allows for direct consideration of uncertainty. Based on this condition we present an approach for the analysis and certification of diagnosability. Furthermore, we propose an approach for the redesign of initially given fault classifications in the parameter space. Specifically we compute diagnosable subsets of initially given parameter sets in polynomial discrete-time fault candidates by comparing pairs of fault candidates. Furthermore, we demonstrate the presented approach for a numerical example.
Serum was obtained from 25 male renal cell carcinoma(RCC) patients and 21 healthy males.O-glycans were released by a-elimination reaction and purified by graphitized carbon cartridge solid phase extraction,then profil...
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Serum was obtained from 25 male renal cell carcinoma(RCC) patients and 21 healthy males.O-glycans were released by a-elimination reaction and purified by graphitized carbon cartridge solid phase extraction,then profiled by matrix-assisted laser desorption/ionisation-time of flight mass *** noise removal and peak alignment,1372 peaks were extracted from 200000 data *** peaks were analyzed by calculation of differential sensitivity and *** combination of two feature peaks was chosen as a biomarker and could clearly differentiate RCC and normal samples in our study group.
This paper presents an insight into leather manufacturing processes, depicting peculiarities and challenges faced by leather industry. An analysis of this industry reveals the need for a new approach to optimize the p...
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Obtaining initial conditions and parameterizations leading to a model consistent with available measurements or safety specifications is important for many applications. Examples include model (in-)validation, predict...
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ISBN:
(纸本)9781467357159
Obtaining initial conditions and parameterizations leading to a model consistent with available measurements or safety specifications is important for many applications. Examples include model (in-)validation, prediction, fault diagnosis, and controller design. We present an approach to determine inner- and outer-approximations of the set containing all consistent initial conditions/parameterizations for nonlinear (polynomial) continuous-time systems. These approximations are found by occupation measures that encode the system dynamics and measurements, and give rise to an infinite-dimensional linear program. We exploit the flexibility and linearity of the decision problem to incorporate unknown-but-bounded and pointwise-in-time state and output constraints, a feature which was not addressed in previous works. The infinite-dimensional linear program is relaxed by a hierarchy of LMI problems that provide certificates in case no consistent initial condition/parameterization exists. Furthermore, the applied LMI relaxation guarantees that the approximations converge (almost uniformly) to the true consistent set. We illustrate the approach with a biochemical reaction network involving unknown initial conditions and parameters.
Component mass conservation gives a linear first integral to the dynamic reaction kinetic equations and greatly influences the set of admissible reactions. Therefore, mass conservation can be related to the deficiency...
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Component mass conservation gives a linear first integral to the dynamic reaction kinetic equations and greatly influences the set of admissible reactions. Therefore, mass conservation can be related to the deficiency of the reaction network and thus to its dynamic properties. In particular, it is shown that a mass conserving CRN without isomers and with a full rank complex composition matrix has zero deficiency. The concepts and results are illustrated on the example of the original and the lumped version of Michaelis-Menten kinetics.
The class of isotherm lumped processsystems with constant overall mass in each of its balance volumes is considered in this paper. It is shown that the convection and transfer mechanisms can be described by a mass ac...
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The class of isotherm lumped processsystems with constant overall mass in each of its balance volumes is considered in this paper. It is shown that the convection and transfer mechanisms can be described by a mass action law chemical reaction network (MAL CRN) with only linear kinetics where the in- and outflow terms are represented using the zero complex. This gives rise to a convection and transfer reaction sub-graph that connects atomic complexes consisting of the components in the balance volumes of the system. The real chemical reactions in each of the balance volumes can be described by their own CRNs, where the chemical reaction sub-graphs may be disconnected from the convection and transfer reaction sub-graph when nonlinear reactions occur. In the case of chemical reactions with a finite number of steady state points, the underlying linear dynamical system enables us to construct a dynamically similar linear overall reaction graph for the whole process system. The resulting overall reaction graph can be used for structural stability analysis by applying its graph theoretical properties.
We introduce a simple approach to account for the ATP consumption and production in the case of mass action models of metabolic pathways including protein turnover. Under some simplifying assumptions, the method makes...
We introduce a simple approach to account for the ATP consumption and production in the case of mass action models of metabolic pathways including protein turnover. Under some simplifying assumptions, the method makes it possible to characterize the optimal rate of enzyme synthesis if the substrate concentrations and other rate constants are known. Furthermore we demonstrate that the proposed approach is capable of the comparison of the efficiency of different feedback laws in dynamic environment, considering time-varying substrate concentration.
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