This paper investigates the problem of fault detection for nonlinear discrete-time networked systems under an event-triggered scheme. A polynomial fuzzy fault detection filter is designed to generate ...a residual signal and detect faults in the system. A novel polynomial event-triggered scheme is proposed to determine the transmission of the signal. A fault detection filter is designed to guarantee that the residual system is asymptotically stable and satisfies the desired performance. Polynomial approximated membership functions obtained by Taylor series are employed for filtering analysis. Furthermore, sufficient conditions are represented in terms of sum of squares (SOSs) and can be solved by SOS tools in MATLAB environment. A numerical example is provided to demonstrate the effectiveness of the proposed results.
Core Ideas
Heihe was the first basin‐scale integrated observatory network established in China.
An intensive flux observation matrix experiment was conducted.
New techniques, e.g., wireless sensor ...network, flux matrix, and airborne remote sensing, are used.
The integrated observatory network is useful in land surface processes research.
Research on land surface processes at the catchment scale has drawn much attention over the past few decades, and a number of watershed observatories have been established worldwide. The Heihe River Basin (HRB), which contains the second largest inland river in China, is an ideal natural field experimental area for investigation of land surface processes involving diverse landscapes and the coexistence of cold and arid regions. The Heihe Integrated Observatory Network was established in 2007. For long‐term observations, a hydrometeorological observatory, ecohydrological wireless sensor network, and satellite remote sensing are now in operation. In 2012, a multiscale observation experiment on evapotranspiration over heterogeneous land surfaces was conducted in the midstream region of the HRB, which included a flux observation matrix, wireless sensor network, airborne remote sensing, and synchronized ground measurements. Under an open data policy, the datasets have been publicly released following careful data processing and quality control. The outcomes highlight the integrated research on land surface processes in the HRB and include observed trends, scaling methods, high spatiotemporal resolution remote sensing products, and model–data integration in the HRB, all of which are helpful to other endorheic basins in the “Silk Road Economic Belt.” Henceforth, the goal of the Heihe Integrated Observatory Network is to develop an intelligent monitoring system that incorporates ground‐based observatory networks, unmanned aerial vehicles, and multi‐source satellites through the Internet of Things technology. Furthermore, biogeochemical processes observation will be improved, and the study of integrating ground observations, remote sensing, and large‐scale models will be promoted further.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
The adaptive fixed-time consensus problem for a class of nonlinear multi-agent systems (MASs) with actuator faults is considered in this paper. To approximate the unknown nonlinear functions in MASs, ...radial basis function neural networks are used. In addition, the first order sliding mode differentiator is utilized to solve the "explosion of complexity" problem, and a filter error compensation method is proposed to ensure the convergence of filter error in fixed time. With the help of the Nussbaum function, the actuator failure compensation mechanism is constructed. By designing the adaptive fixed-time controller, all signals in MASs are bounded, and the consensus errors between the leader and all followers converge to a small area of origin. Finally, the effectiveness of the proposed control method is verified by simulation examples.
In this paper, the stability of polynomial-fuzzy-model-based (PFMB) systems equipped with mismatched interval type-2 (IT2) membership functions is investigated. Unlike the ...membership-function-independent methods, the information and properties of IT2 membership functions are considered in the stability analysis and contained in the stability conditions in terms of sum-of-squares (SOS) based on the Lyapunov stability theory. Three methods, demonstrating their own advantages, are proposed to conduct the stability analysis for the IT2 PFMB control systems. In the first one, we divide the operating domain into subdomains and then conduct the stability analysis incorporating the information and properties of the IT2 membership functions in subdomains. Through this approach, the stability conditions can be further relaxed compared with the membership-function-independent analysis. Polynomial functions are adopted in the second method to approximate the IT2 membership functions. The advantage of this method compared with the first one is that richer information of IT2 membership functions is considered without increasing the number of SOS conditions. In the third one, we combine the advantages of both the first and the second method offering a new approach which utilizes the information and properties of the lower and upper IT2 membership functions in subdomains through simpler polynomial approximation functions. It can be shown that more relaxed stability conditions can be obtained compared with the first two methods. Numerical examples and simulations are presented to verify the effectiveness of the proposed methods.
A mesoporous SBA-15 supported sulfonic acid catalyst (SBA-15-SO3H) was successfully prepared and used for the selective conversion of fructose to 5-hydroxymethylfurfural (HMF). Up to 96% of HMF ...selectivity with 100% fructose conversion was obtained under mild conditions (120 °C, 60 min, DMSO as solvent). Solvent effect, reaction time, reaction temperature and fructose-to-catalysts mass ratio have been investigated. The SBA-15-SO3H solid acid catalyst can be separated from the reaction mixture after reaction and reused by simple centrifugalization, and 100% fructose conversion with 95% HMF yield could be retained. Further, reaction activation energy of 56.4 kJ/mol has been fitted with kinetic analysis, which means that the dehydration of fructose into HMF is relative easier over SBA-15-SO3H catalyst in this work. Besides, X-ray diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR) and scanning electron microscopy (SEM) measurements reveal that the –SO3H grafting on the SBA-15 surface have no obvious influence on its mesoporous structure even after five catalytic cycles, and acid site measurements demonstrate that there was no significant loss of acid site concentration, indicating high catalytic stability. This fruit give a useful reference to chemical engineering and materials, besides future energy and smart city.
•An efficient mesoporous SBA-15 supported sulfonic acid catalyst (SBA-15-SO3H).•Up to 96% HMF yield with 100% fructose conversion could be achieved.•Fructose solubility and solvent polar play work together on SBA-15-SO3H activity.•The reaction activation energy for fructose is 56.4 kJ/mol which is lower than previous reports.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
This paper is concerned with the event-triggered H ∞ control problem for discrete-time nonlinear networked control systems with unreliable communication links. First, an event-triggered scheme is ...proposed to determine whether the sampled data should be released into the network or not. Second, when the released data is transmitted in the network, a Bernoulli process is employed to model the phenomenon of data losses. Third, considering the instants at which the sampled data is not released or data losses occur, a new random process is first developed to model the input data sequence of the controller under the effect of the buffer. Consequently, a novel method is presented to address the stability analysis and control synthesis problems based on the polynomial fuzzy model approach. Finally, some simulation results are given to illustrate the effectiveness of the proposed method.
In this paper, the formation control problem is investigated for a team of uncertain underactuated surface vessels (USVs) based on a directed graph. Considering the risk of collision and the limited ...communication range of USVs, the prescribed performance control (PPC) methodology is employed to ensure collision avoidance and connectivity maintenance. An event-triggered mechanism is designed to reasonably use the limited communication resources. Moreover, neural networks (NNs) and an auxiliary variable are constructed to deal with the problems of uncertain nonlinearities and underactuation, respectively. Then, an event-triggered formation control scheme is proposed to ensure that all signals of the closed-loop system are uniformly ultimately bounded (UUB). Finally, simulation results are presented to demonstrate the effectiveness of the proposed control scheme.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
This paper focuses on the problem of fault detection for Takagi-Sugeno fuzzy systems with time-varying delays via delta operator approach. By designing a filter to generate a residual signal, the ...fault detection problem addressed in this paper can be converted into a filtering problem. The time-varying delay is approximated by the two-term approximation method. Fuzzy augmented fault detection system is constructed in δ-domain, and a threshold function is given. By applying the scaled small gain theorem and choosing a Lyapunov-Krasovskii functional in δ-domain, a sufficient condition of asymptotic stability with a prescribed H ∞ disturbance attenuation level is derived for the proposed fault detection system. Then, a solvability condition for the designed fault detection filter is established, with which the desired filter can be obtained by solving a convex optimization problem. Finally, an example is given to demonstrate the feasibility and effectiveness of the proposed method.
When using linguistic approaches to solve decision problems, we need linguistic representation models. The symbolic model, the 2-tuple fuzzy linguistic representation model and the continuous ...linguistic model are three existing linguistic representation models based on position indexes. Together with these three linguistic models, the corresponding ordered weighted averaging operators, such as the linguistic ordered weighted averaging operator, the 2-tuple ordered weighted averaging operator and the extended ordered weighted averaging operator, have been developed, respectively. In this paper, we analyze the internal relationship among these operators, and propose a consensus operator under the continuous linguistic model (or the 2-tuple fuzzy linguistic representation model). The proposed consensus operator is based on the use of the ordered weighted averaging operator and the deviation measures. Some desired properties of the consensus operator are also presented. In particular, the consensus operator provides an alternative consensus model for group decision making. This consensus model preserves the original preference information given by the decision makers as much as possible, and supports consensus process automatically, without moderator.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Visualizing and perturbing neural activity on a brain-wide scale in model animals and humans is a major goal of neuroscience technology development. Established electrical and optical techniques ...typically break down at this scale due to inherent physical limitations. In contrast, ultrasound readily permeates the brain, and in some cases the skull, and interacts with tissue with a fundamental resolution on the order of 100 μm and 1 ms. This basic ability has motivated major efforts to harness ultrasound as a modality for large-scale brain imaging and modulation. These efforts have resulted in already-useful neuroscience tools, including high-resolution hemodynamic functional imaging, focused ultrasound neuromodulation, and local drug delivery. Furthermore, recent breakthroughs promise to connect ultrasound to neurons at the genetic level for biomolecular imaging and sonogenetic control. In this article, we review the state of the art and ongoing developments in ultrasonic neurotechnology, building from fundamental principles to current utility, open questions, and future potential.
The physics of ultrasound provides noninvasive access to the intact brain and the potential for large-scale imaging and control of neural activity. This article reviews the current state of ultrasound applications in neuroscience, building from fundamental principles to established techniques for functional imaging and neuromodulation and highlighting ongoing technology development to connect ultrasound to neural activity at the molecular level.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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