Academic literature on the topic 'Distribution H∞ filtering'

This paper investigates the distributed H ∞ consensus filtering issue for a class of distributed parameter systems with bounded disturbance. In a framework of optimizing performance, a new approach to improving filter performance is proposed by employing mobile sensor networks. Moreover, the information missing in mobile sensor networks is modeled as a conditional probability distribution. The aim of the filtering challenge is to construct a distributed consensus filter such that the filtering error system is globally asymptotically stable in the mean square, and what disturbances do to the estimation accuracy is attenuated at the H ∞ consensus performance level. Utilizing the Lyapunov direct approach and the spatial operator technique, several sufficient criteria are given for the proposed filter to satisfy the H ∞ consensus performance constraint. Finally, a numerical simulation is given to demonstrate the effectiveness of the design scheme of the proposed filter.

This paper is concerned with the distributed field estimation problem using a sensor network, and the main purpose is to design a local filter for each sensor node to estimate a spatially-distributed physical process using the measurements of the whole network. The finite element method is employed to discretize the infinite dimensional process, which is described by a partial differential equation, and an approximate finite dimensional linear system is established. Due to the sparsity on the spatial distribution of the source function, the ℓ 1 -regularized H ∞ filtering is introduced to solve the estimation problem, which attempts to provide better performance than the classical centralized Kalman filtering. Finally, a numerical example is provided to demonstrate the effectiveness and applicability of the proposed method.

This paper presents the research that was aimed at examining the possibilities for improving the multifractal method for detecting early reflections in the room impulse response. Multifractal method for the detection of early reflections uses distribution of H?lder?s exponent calculated for the acoustic impulse response. Modifications of algorithm proposed in this paper perform filtering of the distribution of H?lder?s exponent to improve the detection of significant early reflections. The results obtained in this way provide guidance how to improve detection of early reflections and to make it more precise.

AbstractHerbaceous plants are often under-studied in tropical forests, despite their high density and diversity, and little is known about the factors that influence their distribution at microscales. In a 25-ha plot in lowland Amazonian rain forest in Yasuní National Park, Ecuador, we censused six species of Heliconia (Heliconiaceae) in a stratified random manner across three topographic habitat types. We observed distribution patterns consistent with habitat filtering. Overall, more individuals occurred in the valley (N = 979) and slope (N = 847) compared with the ridge (N = 571) habitat. At the species level, Heliconia stricta (N = 1135), H. spathocircinata (N = 309) and H. ortotricha (N = 36) all had higher abundance in the valley and slope than ridge. Further, H. vellerigera (N = 20) was completely absent from the ridge. Conversely, H. velutina (N = 903) was most common in the drier ridge habitat. The two most common species (H. stricta and H. velutina) had a reciprocal or negative co-occurrence pattern and occurred preferentially in valley versus ridge habitats. These results suggest that taxa within this family have different adaptations to the wetter valley versus the drier ridge and that habitat partitioning contributes to coexistence.

The problem of statistical fault diagnosis for the quadruple watertanks system is examined. The solution of the fault diagnosis problem for the dynamic model of the four-water tanks system is a non-trivial case, due to nonlinearities and the system’s multivariable structure. In the article’s approach, the system’s dynamic model undergoes first approximate linearization around a temporary operating point which is recomputed at each sampling period. The linearization procedure relies on Taylor series expansion and on the computation of the Jacobian matrices of the state-space description of the system. The H-infinity Kalman Filter is used as a robust state estimator for the approximately linearized model of the quadruple water tanks system. By comparing the outputs of the H-infinity Kalman Filter against the outputs measured from the real water tanks system the residuals sequence is generated. It is concluded that the sum of the squares of the residuals’ vectors, being weighted by the inverse of the associated covariance matrix, stands for a stochastic variable that follows the χ2 distribution. As a consequence, a statistical method for condition monitoring of the quadruple water tanks system is drawn, by using the properties of the χ2 distribution and the related confidence intervals. Actually, normal functioning can be ensured as long as the value of the aforementioned stochastic variable stays within the previously noted confidence intervals. On the other side, one can infer the malfunctioning of the quadruple water tanks system with a high level of certainty (e.g. of the order of 96% to 98%), when these confidence intervals are exceeded. The article’s method allows also for fault isolation, that is for identifying the specific component of the quadruple water tanks system that has been subject to fault or cyber-attack.

The aim of this study was to evaluate in vitro skin permeation and deposition, in vivo toxicokinetics, percutaneous absorption and tissue distribution of benzophenone-3 (BP-3) in rats. Four transdermal formulations containing BP-3 were prepared and evaluated for in vitro skin permeation and deposition of BP-3 using Franz diffusion cells. A gel formulation was used in subsequent in vivo percutaneous absorption due to its high in vitro skin permeation and deposition. Compared to intravenous (i.v.) injection, the prolonged terminal t1/2 (3.1 ± 1.6 h for i.v. injection and 18.3 ± 5.8 h for topical application) was observed indicating occurrence of flip-flop kinetics after topical application. The bioavailability of BP-3 after topical application was 6.9 ± 1.8%. The tissue-to-plasma partition coefficient (kp) for testis, considered a toxic target for BP-3, was less than 1.. Overall, findings of this study may be useful for risk assessment of BP-3.

The present work describes some new improvements concerning the analysis of cement hydration processes using `pencil-beam' synchrotron X-ray diffraction tomography. (i) A new filtering procedure, applied to the diffraction images, has been developed to separate the powder-like contribution from that of the grains in the diffraction images. (ii) In addition to improving the quality of the diffraction images for the subsequent analysis and tomographic reconstruction, the filtering procedure can also be used to perform a qualitative analysis of the crystallite size distribution, whenever the more standard approaches cannot be applied. (iii) Given the importance of the calcium silicate hydrate phase (C–S–H) in cements, a procedure to obtain its spatial distribution using the diffraction signal has been successfully applied, even though C–S–H is a highly disordered phase, almost amorphous to X-ray diffraction. (iv) The main result of this study has been to show that, in spite of the long measurement times required, it is possible to usein situexperiments at different aging times of cement pastes to monitor the cement evolution. This allowed the evolution of the microstructure during the acceleration and deceleration periods of the hydration process to be checked with unprecedented detail, since the quantitative spatial distribution of each phase (including C–S–H) dissolved or precipitated in the sample has been obtained. The reported approach opens up a range of opportunities for the investigation of complex multiphase systems and processes, including hydration and microstructural development in cements.

This paper concentrates on the event-triggered H ∞ filter design for the discrete-time Markovian jump neural networks under random missing measurements and cyber attacks. Considering that the controlled system and the filtering can exchange information over a shared communication network which is vulnerable to the cyber attacks and has limited bandwidth, the event-triggered mechanism is proposed to relieve the communication burden of data transmission. A variable conforming to Bernoulli distribution is exploited to describe the stochastic phenomenon since the missing measurements occur with random probability. Furthermore, seeing that the communication networks are vulnerable to external malicious attacks, the transferred information via the shared communication network may be changed by the injected false information from the attackers. Based on the above consideration, sufficient conditions for the filtering error system to maintain asymptotically stable are provided with predefined H ∞ performance. In the end, three numerical examples are given to verify the proposed theoretical results.

Networked systems are systems in which data transmissions among system components are completed through communication networks. As one fundamental issue, distributed filtering of networked systems has gained growing attention in the fields of control and signal processing, and its objective is to estimate system states using noisy output measurements. Thus, distributed filtering for networked systems has found a wide range of applications in areas such as health care monitoring, security detecting, industrial process automation, and environmental monitoring. A defining feature of distributed filtering is that connections among nodes of a distributed system is completed through communication networks rather than point-to-point cables. Compared with traditional point-to-point connections, communication networks can bring several advantages, e.g. low cost, high reliability, ease of maintenance and reconfiguration, and flexible system architecture, especially for distributed systems, where sensors, actuators and controllers are spatially distributed far away from each other. However, communication networks may have some challenging issues, which make the distributed filtering problem complicated. First, because of limited bandwidth, network-induced delays and packet dropouts are unavoidable, which usually deteriorate the system performance. Second, due to the dynamic characteristics of networks, the topology of a distributed system is not fixed, which is difficult to be dealt with when current system states are estimated. Third, as a result of limited network resources, the network traffic may be congested if all the sampling periods of sensor nodes are very small, which is undesired in the distributed filtering. Therefore, it is significant to address the problem of distributed filtering by taking the above challenging issues into account, which motivates this study. This thesis is concerned with distributed filtering for networked systems. Several results have been reported on the effects of network-induced constraints including delays and packet dropouts, dynamic topologies, and network resource utilizations, on the performance of distributed H∞ filtering error system. More specifically, the emphasis is placed on the following four aspects: • Event-triggered distributed H∞ filtering. In order to save limited network resources, a distributed event-triggered transmission scheme is introduced to choose those necessary data packets to be transmitted among neighboring filters. Under the event-triggered transmission scheme, the resultant filtering error system is modeled as a time-delay system. By employing Lyapunov- Krasovskii functional method, both event-triggered parameters and distributed H∞ filter parameters can be designed in terms of linear matrix inequalities. • Distributed H∞ filtering for continuous-time systems over sensor networks with dynamical topologies. The distributed H∞ filtering for continuous-time systems over sensor networks is investigated. On the one hand, the effects of data packet dropouts on the distributed H∞ filtering are investigated. On the other hand, a novel distributed event-triggered scheme is introduced to transmit those necessary data packets in the case that the topology of the sensor network is dynamic. Moreover, algorithms are also given to design suitable distributed H∞ filters. • Event-triggered distributed H∞ filtering for multi-rate systems subject to data packet dropouts. For multi-rate distributed systems, event-triggered distributed H∞ filtering is studied by taking packet dropouts into account. By applying a lifting technique, the resultant multi-rate distributed filtering error system is transformed into a high dimensional single-rate system. As a result, novel sufficient conditions are established such that the distributed filtering error system is mean-square exponentially stable with a desired H∞ attenuation level. Moreover, an iterative algorithm is presented for the design of both distributed filters and event-triggered parameters. • Event-triggered distributed H∞ filtering for sensor networks under Round-Robin scheduling. Event-triggered distributed H∞ filtering for sensor networks is investigated under Round-Robin scheduling. Each sensor is equipped with a few samplers, and the scheduling of signals from samplers to filters is ruled by the classical Round-Robin protocol. In order to save precious network resources, a novel event-triggered transmission scheme is presented, where network-induced delays are taken into account. Moreover, the resultant filtering error system is modeled as a switched system with multiple time-varying delays. Switched system approaches are thus employed to design distributed H∞ filters based on a set of LMIs. Several simulation results are provided to validate the proposed methods.

The aerodynamic noise sources around the three dimensional bump are studied. In this search, pressure fluctuation on the wall which effects interior noise is searched using ILES. The ratio of the bump diameter (D) and height (H) is D/H = 4. In front of the bump, the boundary layer thickness is half of the bump height. Reynolds number based on the bump height was 65000 and the free stream Mach number is 0.1. In flow boundary layer profile is given by using rescaling method and the laminar boundary layer is changed into turbulent boundary layer. Sixth-order-accurate compact scheme is used to represent spatial derivatives and six-order low pass spatial filtering procedure is utilized for removing numerical oscillations. First, instantaneous flow field is discussed. Second, characteristics of time average flow field, such as Cp distribution and stream line topology, are discussed. Third, spanwise velocity fluctuation and sound pressure level on the wall are discussed.