Model-based Optimal Control of Variable Air Volume Terminal Box

In the U.S. A Variable Air Volume (VAV) system is one of most commonly used air system for multiple-zone commercial buildings due to its capability to meet the varying heating and cooling loads of different building thermal zones. One of key component of VAV system is the terminal VAV box. There are an air damper and a reheat coil in the box. How to effectively and efficiently control the VAV box plays a significant role to reduce energy consumption and maintain acceptable indoor environment in buildings. Currently, there are two control logics used for controlling VAV box, namely, single maximum and dual maximum control logics. The single maximum logic is the most common, where the room temperature setpoint is maintained by only adjusting the reheat coil valve position in the heating model. The damper position is kept as the minimal to satisfy the ventilation requirement only. On the other hand, the more advanced dual maximum control logic realizes the room air temperature control by adjusting both damper position and reheat coil valve position in the heating model. For the cooling model, both control logics have the same action to maintain room air temperature setpoint through adjusting the damper position. Â In this study, a model-based optimal control is explored to minimize the energy consumption of the VAV box with a hot water reheat coil. Data driven approach based on an Autoregressive exogenous (ARX) model is investigated to represent dynamics of the room thermal response. The similar data-driven approach is used to develop an energy consumption model of the VAV box. Measured data for the VAV box from a real building is used to train and test data-driven model. Such data includes room air temperature, outdoor air temperature, supply air temperature, supply air flow rate, damper position, reheat coil valve position and VAV box energy consumption. A platform of AMPL (A Modeling Language for Mathematical Programming) is used to for mathematical modeling and links to different optimization solvers. Â In addition, uncertainty analysis and sensitivity analysis are conducted to help understand the model behaviors and performance. In this study, the Monte Carlo sampling method is applied to generate samples for model inputs including supply air temperature, outdoor conditions, etc. A quantified sensitivity index of Sobol is calculated to indicate the impact level from different inputs or disturbances

A note on control of a class of discrete-time stochastic systems with distributed delays and nonlinear disturbances

The official published version of this article can be found at the link below.This paper is concerned with the state feedback control problem for a class of discrete-time stochastic systems involving sector nonlinearities and mixed time-delays. The mixed time-delays comprise both discrete and distributed delays, and the sector nonlinearities appear in the system states and all delayed states. The distributed time-delays in the discrete-time domain are first defined and then a special matrix inequality is developed to handle the distributed time-delays within an algebraic framework. An effective linear matrix inequality (LMI) approach is proposed to design the state feedback controllers such that, for all admissible nonlinearities and time-delays, the overall closed-loop system is asymptotically stable in the mean square sense. Sufficient conditions are established for the nonlinear stochastic time-delay systems to be asymptotically stable in the mean square sense, and then the explicit expression of the desired controller gains is derived. A numerical example is provided to show the usefulness and effectiveness of the proposed design method.This work was supported in part by the Engineering and Physical Sciences Research Council (EPSRC) of the U.K. under Grant GR/S27658/01, the Royal Society of the U.K., the National Natural Science Foundation of China under Grants 60774073 and 60974030, the National 973 Program of China under Grant 2009CB320600, and the Alexander von Humboldt Foundation of Germany

Robust H∞ control for a class of nonlinear discrete time-delay stochastic systems with missing measurements

This is the post print version of the article. The official published version can be obtained from the link - Copyright 2009 Elsevier LtdThis paper is concerned with the problem of robust H∞ output feedback control for a class of uncertain discrete-time delayed nonlinear stochastic systems with missing measurements. The parameter uncertainties enter into all the system matrices, the time-varying delay is unknown with given low and upper bounds, the nonlinearities satisfy the sector conditions, and the missing measurements are described by a binary switching sequence that obeys a conditional probability distribution. The problem addressed is the design of an output feedback controller such that, for all admissible uncertainties, the resulting closed-loop system is exponentially stable in the mean square for the zero disturbance input and also achieves a prescribed H∞ performance level. By using the Lyapunov method and stochastic analysis techniques, sufficient conditions are first derived to guarantee the existence of the desired controllers, and then the controller parameters are characterized in terms of linear matrix inequalities (LMIs). A numerical example is exploited to show the usefulness of the results obtained.This paper was not presented at any IFAC meeting. This paper was recommended for publication in revised form by Associate Editor Dragan Nešic under the direction of Editor Hassan K. Khalil. This work was supported in part by the Engineering and Physical Sciences Research Council (EPSRC) of the U.K. under Grant GR/S27658/01, the City University of Hong Kong under Grant 7001992, the Royal Society of the U.K. under an International Joint Project, the Natural Science Foundation of Jiangsu Province of China under Grant BK2007075, the National Natural Science Foundation of China under Grant 60774073, and the Alexander von Humboldt Foundation of Germany

Remodeling of the periodontal ligament and alveolar bone during axial tooth movement in mice with type 1 diabetes

ObjectivesTo observe the elongation of the axial tooth movement in the unopposed rodent molar model with type 1 diabetes mellitus and explore the pathological changes of periodontal ligament and alveolar bone, and their correlation with tooth axial movement.MethodsThe 80 C57BL/6J mice were randomly divided into the streptozotocin(STZ)-injected group (n = 50) and the control group (n = 30). Mice in the streptozotocin(STZ)-injected group were injected intraperitoneal with streptozotocin (STZ), and mice in the control group were given intraperitoneal injection of equal doses of sodium citrate buffer. Thirty mice were randomly selected from the successful models as the T1DM group. The right maxillary molar teeth of mice were extracted under anesthesia, and allowed mandibular molars to super-erupt. Mice were sacrificed at 0, 3, 6,9, and 12 days. Tooth elongation and bone mineral density (BMD) were evaluated by micro-CT analysis(0,and 12 days mice). Conventional HE staining, Masson staining and TRAP staining were used to observe the changes in periodontal tissue(0, 3, 6, 9, and 12 days mice). The expression differences of SPARC, FGF9, BMP4, NOGGIN, and type I collagen were analyzed by RT-qPCR.ResultsAfter 12 days of tooth extraction, our data showed significant super-eruption of mandibular mouse molars of the two groups. The amount of molar super-eruption in the T1DM group was 0.055mm( ± 0.014mm), and in the control group was 0.157( ± 0.017mm). The elongation of the T1DM mice was less than that of the control mice(P<0.001). It was observed that the osteoclasts and BMD increased gradually in both groups over time. Compared with the control group, the collagen arrangement was more disordered, the number of osteoclasts was higher (P<0.05), and the increase of bone mineral density was lower(2.180 ± 0.007g/cm3 vs. 2.204 ± 0.006g/cm3, P<0.001) in the T1DM group. The relative expression of SPARC, FGF9, BMP4, and type I collagen in the two groups increased with the extension of tooth extraction time while NOGGIN decreased. The relative expression of all of SPARC, FGF9, BMP4, and type I collagen in the T1DM group were significantly lower, and the expression of NOGGIN was higher than that in the control group (P<0.05).ConclusionThe axial tooth movement was inhibited in type 1 diabetic mice. The result may be associated with the changes of periodontal ligament osteoclastogenic effects and alveolar bone remodeling regulated by the extracellular matrix and osteogenesis-related factors

Horizontally Acquired Polysaccharide-Synthetic Gene Cluster From Weissella cibaria Boosts the Probiotic Property of Lactiplantibacillus plantarum

Lactiplantibacillus plantarum are probiotic bacteria, maintaining the integrity of the gastrointestinal epithelial barrier, and preventing the infection of pathogenic bacteria. Exopolysaccharides (EPSs) are often involved in the probiotic property of L. plantarum. Here, we identified a new EPS-synthetic gene cluster, cpsWc, carrying 13 genes, laid on a large plasmid in a well-characterized probiotic L. plantarum strain LTC-113. The cpsWc gene cluster was horizontally acquired from Weissella cibaria, enhancing the biofilm formation ability of the host strain and its tolerance to harsh environmental stresses, including heat, acid, and bile. Transfer of cpsWc also conferred the probiotic properties to other L. plantarum strains. Moreover, cpsWc strengthened the adhesion of LTC-113 to intestinal epithelial cells. Both the cpsWc-carrying LTC-113 and its EPSs per se effectively attenuated the LPS-induced pro-inflammatory effect of intestinal epithelial cells, and inhibited the adhesion of pathogenic bacteria, such as S. typhimurium and E. coli by exclusion and competition. The newly identified cpsWc gene cluster emphasized the contribution of mobile EPS-synthetic element on the probiotic activity of L. plantarum, and shed a light on the engineering of probiotic bacteria

Comprehensive evaluations of a prototype full field-of-view photon counting CT system through phantom studies

Photon counting CT (PCCT) has been a research focus in the last two decades. Recent studies and advancements have demonstrated that systems using semiconductor-based photon counting detectors (PCDs) have the potential to provide better contrast, noise and spatial resolution performance compared to conventional scintillator-based systems. With multi-energy threshold detection, PCD can simultaneously provide the photon energy measurement and enable material decomposition for spectral imaging. In this work, we report a performance evaluation of our first CdZnTe-based prototype full-size photon counting CT system through various phantom imaging studies. This prototype system supports a 500 mm scan field-of-view (FOV) and 10 mm cone coverage at isocenter. Phantom scans were acquired using 120 kVp from 50 to 400 mAs to assess the imaging performance on: CT number accuracy, uniformity, noise, spatial resolution, material differentiation and quantification. Both qualitative and quantitative evaluations show that PCCT has superior image quality with lower noise and improved spatial resolution compared to conventional energy integrating detector (EID)-CT. Using projection domain material decomposition approach with multiple energy bin measurements, PCCT virtual monoenergetic images (VMIs) have lower noise, and superior performance in quantifying iodine and calcium concentrations. These improvements lead to increased contrast-to-noise ratio (CNR) for both high and low contrast study objects and can significantly reduce the iodine contrast agent to achieve the same CNR as EID-CT. PCCT can also generate super-high resolution (SHR) images using much smaller detector pixel size than EID-CT and dramatically push the spatial resolution limit. These initial results demonstrate that PCCT based on CdZnTe detectors has huge potential in clinical settings