Multi-Objective Robust H-infinity Control of Spacecraft Rendezvous

Based on the relative motion dynamic model illustrated by C-W equations, the problem of robust Hinfin control for a class of spacecraft rendezvous systems is investigated, which contains parametric uncertainties, external disturbances and input constraints. An Hinfin state-feedback controller is designed via a Lyapunov approach, which guarantees the closed-loop system to meet the multi-objective design requirements. The existence conditions for admissible controllers are formulated in the form of linear matrix inequalities (LMIs), and the controller design is cast into a convex optimization problem subject to LMI constraints. An illustrative example is provided to show the effectiveness of the proposed control design method

Optimizing the thermoelectric performance of zigzag and chiral carbon nanotubes

Using nonequilibrium molecular dynamics simulations and nonequilibrium Green's function method, we investigate the thermoelectric properties of a series of zigzag and chiral carbon nanotubes which exhibit interesting diameter and chirality dependence. Our calculated results indicate that these carbon nanotubes could have higher ZT values at appropriate carrier concentration and operating temperature. Moreover, their thermoelectric performance can be significantly enhanced via isotope substitution, isoelectronic impurities, and hydrogen adsorption. It is thus reasonable to expect that carbon nanotubes may be promising candidates for high-performance thermoelectric materials

Probability-guaranteed H∞ finite-horizon filtering for a class of nonlinear time-varying systems with sensor saturations

This is the Post-Print version of the Article. The official published version can be accessed from the link below - Copyright @ 2012 ElsevierIn this paper, the probability-guaranteed H∞ finite-horizon filtering problem is investigated for a class of nonlinear time-varying systems with uncertain parameters and sensor saturations. The system matrices are functions of mutually independent stochastic variables that obey uniform distributions over known finite ranges. Attention is focused on the construction of a time-varying filter such that the prescribed H∞ performance requirement can be guaranteed with probability constraint. By using the difference linear matrix inequalities (DLMIs) approach, sufficient conditions are established to guarantee the desired performance of the designed finite-horizon filter. The time-varying filter gains can be obtained in terms of the feasible solutions of a set of DLMIs that can be recursively solved by using the semi-definite programming method. A computational algorithm is specifically developed for the addressed probability-guaranteed H∞ finite-horizon filtering problem. Finally, a simulation example is given to illustrate the effectiveness of the proposed filtering scheme.This work was supported in part by the National Natural Science Foundation of China under Grants 61028008, 60825303 and 60834003, National 973 Project under Grant 2009CB320600, the Fok Ying Tung Education Fund under Grant 111064, the Special Fund for the Author of National Excellent Doctoral Dissertation of China under Grant 2007B4, the Key Laboratory of Integrated Automation for the Process Industry (Northeastern University) from the Ministry of Education of China, the Engineering and Physical Sciences Research Council (EPSRC) of the U.K. under Grant GR/S27658/01, the Royal Society of the U.K., and the Alexander von Humboldt Foundation of Germany

Robust H-infinity filtering for 2-D systems with intermittent measurements

This paper is concerned with the problem of robust H∞ filtering for uncertain two-dimensional (2-D) systems with intermittent measurements. The parameter uncertainty is assumed to be of polytopic type, and the measurements transmission is assumed to be imperfect, which is modeled by a stochastic variable satisfying the Bernoulli random binary distribution. Our attention is focused on the design of an H∞ filter such that the filtering error system is stochastically stable and preserves a guaranteed H∞ performance. This problem is solved in the parameter-dependent framework, which is much less conservative than the quadratic approach. By introducing some slack matrix variables, the coupling between the positive definite matrices and the system matrices is eliminated, which greatly facilitates the filter design procedure. The corresponding results are established in terms of linear matrix inequalities, which can be easily tested by using standard numerical software. An example is provided to show the effectiveness of the proposed approac

The Effect of Fecal Microbiota Transplantation on a Child with Tourette Syndrome

Tourette syndrome is a neuropsychiatric disorder with onset in childhood. New therapies are needed to effectively manage and treat this condition. Gut microbiota can affect central physiology and function via the microbiota-gut-brain axis. Here, we report a case in which fecal microbiota transplantation (FMT) is used to treat a child with Tourette syndrome, whose symptoms ameliorated dramatically in the following eight weeks

Towards name-based trust and security for content-centric network. In

Abstract-Trust and security have been considered as builtin properties for future Internet architecture. Leveraging the concept of named content in recently proposed information centric network, we propose a name-based trust and security protection mechanism. Our scheme is built with identity-based cryptography (IBC), where the identity of a user or device can act as a public key string. Uniquely, in named content network such as content-centric network (CCN), a content name or its prefixes can be used as public identities, with which content integrity and authenticity can be achieved with IBC algorithms. The trust of a content is seamlessly integrated with the verification of the content's integrity and authenticity with its name or prefix, instead of the public key certificate of its publisher. In addition, flexible confidentiality protection is enabled between content publishers and consumers. For scalable deployment purpose, we further propose to use a hybrid scheme combined with traditional public-key infrastructure (PKI) and IBC. We have implemented this scheme with CCNx open source project on Android

Extended Kalman filtering with stochastic nonlinearities and multiple missing measurements

Copyright @ 2012 ElsevierIn this paper, the extended Kalman filtering problem is investigated for a class of nonlinear systems with multiple missing measurements over a finite horizon. Both deterministic and stochastic nonlinearities are included in the system model, where the stochastic nonlinearities are described by statistical means that could reflect the multiplicative stochastic disturbances. The phenomenon of measurement missing occurs in a random way and the missing probability for each sensor is governed by an individual random variable satisfying a certain probability distribution over the interval [0,1]. Such a probability distribution is allowed to be any commonly used distribution over the interval [0,1] with known conditional probability. The aim of the addressed filtering problem is to design a filter such that, in the presence of both the stochastic nonlinearities and multiple missing measurements, there exists an upper bound for the filtering error covariance. Subsequently, such an upper bound is minimized by properly designing the filter gain at each sampling instant. It is shown that the desired filter can be obtained in terms of the solutions to two Riccati-like difference equations that are of a form suitable for recursive computation in online applications. An illustrative example is given to demonstrate the effectiveness of the proposed filter design scheme.This work was supported in part by the National 973 Project under Grant 2009CB320600, National Natural Science Foundation of China under Grants 61028008, 61134009 and 60825303, the State Key Laboratory of Integrated Automation for the Process Industry (Northeastern University) of China, the Engineering and Physical Sciences Research Council (EPSRC) of the U.K. under Grant GR/S27658/01, the Royal Society of the U.K., and the Alexander von Humboldt Foundation of Germany

Proton pump inhibitors induced fungal dysbiosis in patients with gastroesophageal reflux disease

Gut mycobiota inhabits human gastrointestinal lumen and plays a role in human health and disease. We investigated the influence of proton pump inhibitors (PPIs) on gastric mucosal and fecal mycobiota in patients with gastroesophageal reflux diseases (GERD) by using Internal Transcribed Spacer 1 sequencing. A total of 65 participants were included, consisting of the healthy control (HC) group, GERD patients who did not use PPIs (nt-GERD), and GERD patients who used PPIs, which were further divided into short-term (s-PPI) and long-term PPI user (l-PPI) groups based on the duration of PPI use. The alpha diversity and beta diversity of gastric mucosal mycobiota in GERD patients with PPI use were significantly different from HCs, but there were no differences between s-PPI and l-PPI groups. LEfSe analysis identified Candida at the genus level as a biomarker for the s-PPI group when compared to the nt-GERD group. Meanwhile, Candida, Nothojafnea, Rhizodermea, Ambispora, and Saccharicola were more abundant in the l-PPI group than in the nt-GERD group. Furthermore, colonization of Candida in gastric mucosa was significantly increased after PPI treatment. However, there was no significant difference in Candida colonization between patients with endoscopic esophageal mucosal breaks and those without. There were significant differences in the fecal mycobiota composition between HCs and GERD patients regardless whether or not they used PPI. As compared to nt-GERD patient samples, there was a high abundance of Alternaria, Aspergillus, Mycenella, Exserohilum, and Clitopilus in the s-PPI group. In addition, there was a significantly higher abundance of Alternaria, Aspergillus, Podospora, Phallus, and Monographella in the l-PPI group than nt-GERD patients. In conclusion, our study indicates that dysbiosis of mycobiota was presented in GERD patients in both gastric mucosal and fecal mycobiota. PPI treatment may increase the colonization of Candida in the gastric mucosa in GERD patients

Observer-based H∞ control of networked systems with stochastic communication protocol: The finite-horizon case

This paper is concerned with the H ∞ control problem for a class of linear time-varying networked control systems (NCSs) with stochastic communication protocol (SCP). The sensor-to-controller network (the controller-to-actuator network) is considered where only one sensor (one actuator) obtains access to the communication network at each transmission instant. The SCP is applied to determine which sensor (actuator) should be given the access to the network at a certain instant. The aim of the problem addressed is to design an observer-based controller such that the H ∞ performance of the closed-loop system is guaranteed over a given finite horizon. For the purpose of simplifying the NCS model, a new Markov chain is constructed to model the SCP scheduling of communication networks. Then, both the methods of stochastic analysis and completing squares are utilized to establish the sufficient conditions for the existence of the desired controller. The controller parameters are characterized by solving two coupled backward recursive Riccati difference equations subject to the scheduled SCP. Finally, a numerical example is given to illustrate the effectiveness of the proposed controller design scheme