Filtering for networked stochastic time-delay systems with sector nonlinearity

Copyright [2009] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.This paper is concerned with the filtering problem for a class of discrete-time stochastic nonlinear networked control systems with network-induced incomplete measurements. The incomplete measurements include both the multiple random communication delays and random packet losses, which are modeled by a unified stochastic expression in terms of a set of indicator functions that is dependent on certain stochastic variable. The nonlinear functions are assumed to satisfy the sector nonlinearities. The purpose of the addressed filtering problem is to design a linear filter such that the filtering-error dynamics is exponentially mean-square stable. By using the linear-matrix-inequality (LMI) method and delay-dependent technique, sufficient conditions are derived which are dependent on the occurrence probability of both the random communication delays and missing measurement. The filter gain is then characterized by the solution to a set of LMIs. A simulation example is exploited to demonstrate the effectiveness of the proposed design procedures

Effect factors of part-load performance for various Organic Rankine cycles using in engine waste heat recovery

The Organic Rankine Cycle (ORC) is regarded as one of the most promising waste heat recovery technologies for electricity generation engines. Since the engine usually operates under different working conditions, it is important to research the part-load performance of the ORC. In order to reveal the effect factors of part-load performance, four different forms of ORCs are compared in the study with dynamic math models established in SIMULINK. They are the ORC applying low temperature working fluid R245fa with a medium heat transfer cycle, the ORCs with high temperature working fluid toluene heated directly by exhaust condensing at low pressure and high pressure, and the double-stage ORC. It is regarded that the more slowly the system output power decreases, the better part-load performance it has. Based on a comparison among the four systems, the effects of evaporating pressure, condensing condition, working fluid, and system structure on part-load performance are revealed in the work. Further, it is found that the system which best matches with the heat source not only performs well under the design conditions, but also has excellent part-load performance

Robust filtering for gene expression time series data with variance constraints

This is the post print version of the article. The official published version can be obtained from the link below - Copyright 2007 Taylor & Francis Ltd.In this paper, an uncertain discrete-time stochastic system is employed to represent a model for gene regulatory networks from time series data. A robust variance-constrained filtering problem is investigated for a gene expression model with stochastic disturbances and norm-bounded parameter uncertainties, where the stochastic perturbation is in the form of a scalar Gaussian white noise with constant variance and the parameter uncertainties enter both the system matrix and the output matrix. The purpose of the addressed robust filtering problem is to design a linear filter such that, for the admissible bounded uncertainties, the filtering error system is Schur stable and the individual error variance is less than a prespecified upper bound. By using the linear matrix inequality (LMI) technique, sufficient conditions are first derived for ensuring the desired filtering performance for the gene expression model. Then the filter gain is characterized in terms of the solution to a set of LMIs, which can easily be solved by using available software packages. A simulation example is exploited for a gene expression model in order to demonstrate the effectiveness of the proposed design procedures.This work was supported in part by the Engineering and Physical Sciences Research Council (EPSRC) of the UK under Grants GR/S27658/01 and EP/C524586/1, the Biotechnology and Biological Sciences Research Council (BBSRC) of the UK under Grants BB/C506264/1 and 100/EGM17735, the Nuffield Foundation of the UK under Grant NAL/00630/G, and the Alexander von Humboldt Foundation of Germany

Experimental study on transcritical Rankine cycle (TRC) using CO2/R134a mixtures with various composition ratios for waste heat recovery from diesel engines

A carbon dioxide (CO2) based mixture was investigated as a promising solution to improve system performance and expand the condensation temperature range of a CO2 transcritical Rankine cycle (C-TRC). An experimental study of TRC using CO2/R134a mixtures was performed to recover waste heat of engine coolant and exhaust gas from a heavy-duty diesel engine. The main purpose of this study was to investigate experimentally the effect of the composition ratio of CO2/R134a mixtures on system performance. Four CO2/R134a mixtures with mass composition ratios of 0.85/0.15, 0.7/0.3, 0.6/0.4 and 0.4/0.6 were selected. The high temperature working fluid was expanded through an expansion valve and then no power was produced. Thus, current research focused on the analysis of measured operating parameters and heat exchanger performance. Heat transfer coefficients of various heat exchangers using supercritical CO2/R134a mixtures were provided and discussed. These data may provide useful reference for cycle optimization and heat exchanger design in application of CO2 mixtures. Finally, the potential of power output was estimated numerically. Assuming an expander efficiency of 0.7, the maximum estimations of net power output using CO2/R134a (0.85/0.15), CO2/R134a (0.7/0.3), CO2/R134a (0.6/0.4) and CO2/R134a (0.4/0.6) are 5.07 kW, 5.45 kW, 5.30 kW, and 4.41 kW, respectively. Along with the increase of R134a composition, the estimation of net power output, thermal efficiency and exergy efficiency increased at first and then decreased. CO2/R134a (0.7/0.3) achieved the maximum net power output at a high expansion inlet pressure, while CO2/R134a (0.6/0.4) behaves better at low pressure

Tick-borne encephalitis virus induces chemokine RANTES expression via activation of IRF-3 pathway.

BACKGROUND: Tick-borne encephalitis virus (TBEV) is one of the most important flaviviruses that targets the central nervous system (CNS) and causes encephalitides in humans. Although neuroinflammatory mechanisms may contribute to brain tissue destruction, the induction pathways and potential roles of specific chemokines in TBEV-mediated neurological disease are poorly understood. METHODS: BALB/c mice were intracerebrally injected with TBEV, followed by evaluation of chemokine and cytokine profiles using protein array analysis. The virus-infected mice were treated with the CC chemokine antagonist Met-RANTES or anti-RANTES mAb to determine the role of RANTES in affecting TBEV-induced neurological disease. The underlying signaling mechanisms were delineated using RANTES promoter luciferase reporter assay, siRNA-mediated knockdown, and pharmacological inhibitors in human brain-derived cell culture models. RESULTS: In a mouse model, pathological features including marked inflammatory cell infiltrates were observed in brain sections, which correlated with a robust up-regulation of RANTES within the brain but not in peripheral tissues and sera. Antagonizing RANTES within CNS extended the survival of mice and reduced accumulation of infiltrating cells in the brain after TBEV infection. Through in vitro studies, we show that virus infection up-regulated RANTES production at both mRNA and protein levels in human brain-derived cell lines and primary progenitor-derived astrocytes. Furthermore, IRF-3 pathway appeared to be essential for TBEV-induced RANTES production. Site mutation of an IRF-3-binding motif abrogated the RANTES promoter activity in virus-infected brain cells. Moreover, IRF-3 was activated upon TBEV infection as evidenced by phosphorylation of TBK1 and IRF-3, while blockade of IRF-3 activation drastically reduced virus-induced RANTES expression. CONCLUSIONS: Our findings together provide insights into the molecular mechanism underlying RANTES production induced by TBEV, highlighting its potential importance in the process of neuroinflammatory responses to TBEV infection

Effect of cluster thinning on catechins in berries of Vitis vinifera cv. Cabernet Sauvignon

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