This paper investigates the tracking problem for a class of uncertain switched nonlinear delayed systems with nonstrict‐feedback form. To address this problem, by introducing a new common Lyapunov function (CLF), an adaptive neural network dynamic surface control is proposed. The state‐dependent switching rule is designed to orchestrate which subsystem is active at each time instance. In order to compensate unknown delay terms, an appropriate Lyapunov‐Krasovskii functional is considered in the constructing of the CLF. In addition, a novel switched neural network–based observer is constructed to estimate system states through the output signal. To maintain the tracking error performance within a predefined bound, a prescribed performance bound approach is employed. It is proved that by the proposed output‐feedback control, all the signals of the closed‐loop system are bounded under the switching law. Moreover, the transient and steady‐state tracking performance is guaranteed by the prescribed performance bound. Finally, the effectiveness of the proposed method is illustrated by two numerical and practical examples. 相似文献
Mobile ad hoc networks (MANETs) are mobile networks, which are automatically outspread on a geographically limited region, without requiring any preexisting infrastructure. Mostly, nodes are both self-governed and self-organized without requiring a central monitoring. Because of their distributed characteristic, MANETs are vulnerable to a particular routing misbehavior, called wormhole attack. In wormhole attack, one attacker node tunnels packet from its position to the other attacker nodes. Such wormhole attack results in a fake route with fewer hop count. If source node selects this fictitious route, attacker nodes have the options of delivering the packets or dropping them. For this reason, this paper proposes an improvement over AODV routing protocol to design a wormhole-immune routing protocol. The proposed protocol called defending against wormhole attack (DAWA) employs fuzzy logic system and artificial immune system to defend against wormhole attacks. DAWA is evaluated through extensive simulations in the NS-2 environment. The results show that DAWA outperforms other existing solutions in terms of false negative ratio, false positive ratio, detection ratio, packet delivery ratio, packets loss ratio and packets drop ratio. 相似文献
In many network applications such as surveillance systems, it is crucial to detect the target and estimate its location. Distributed processing algorithms are capable of providing fast, secure, scalable and robust solutions. In this paper, we study the problem of target detection and localization in a wireless sensor network. Most of the current researches have focused on centralized algorithms and the works done on distributed algorithms usually need center assistance and practical issues such as communication link failure is not addressed in them. In this paper, we first propose a distributed consensus-based algorithm for target detection and then propose a distributed consensus-based localization algorithm. We assume that the target transmits a radio signal that is received in sensors equipped with limited computational and power resources. We consider the communication link failure and use the collaboration of sensor nodes to detect the presence of target. In the proposed target localization algorithm, sensor nodes estimate their distance toward the target using the received signal strength. In both the proposed algorithms, sensor nodes exchange information only with their neighbors and each makes an individual decision. We further prove the convergence of the proposed algorithms. Computer simulations confirm that the proposed algorithms are very fast and applicable in high-performance networks. We improve the localization accuracy at least by 25 % in terms of localization error compared with some recent algorithms. 相似文献
In this paper, a new representation of neural tensor networks is presented. Recently, state-of-the-art neural tensor networks have been introduced to complete RDF knowledge bases. However, mathematical model representation of these networks is still a challenging problem, due to tensor parameters. To solve this problem, it is proposed that these networks can be represented as two-layer perceptron network. To complete the network topology, the traditional gradient based learning rule is then developed. It should be mentioned that for tensor networks there have been developed some learning rules which are complex in nature due to the complexity of the objective function used. Indeed, this paper is aimed to show that the tensor network can be viewed and represented by the two-layer feedforward neural network in its traditional form. The simulation results presented in the paper easily verify this claim.
Microsystem Technologies - In this article, shear vibration and buckling of double-layer orthotropic nanoplates resting on elastic foundations are analyzed subjected to in-plane loadings including... 相似文献
In this article, an analytical method is presented for thermo-mechanical vibration analysis of functionally graded (FG) nanoplates with different boundary conditions under various thermal loadings including uniform, linear, and nonlinear temperature rise via a four-variable plate theory considering neutral surface position. The temperature-dependent material properties of FG nanoplate vary gradually along the thickness according to the Mori-Tanaka homogenization scheme. The exactness of solution is confirmed by comparing obtained results with those provided in the literature. A parametric study is performed investigating the effects of nonlocal parameter, temperature fields, gradient index, and boundary conditions on vibration behavior of FG nanoplates. 相似文献
In recent years, the problems associated with bacterial resistance to antibiotics caused nanodrugs to be considered as a new way for infectious diseases treatment. The main purpose of this study was to develop a new agent against Pseudomonas aeruginosa, a very difficult bacterium to treat, based on azlocillin antibiotic and silver nanoparticles (AgNPs). Azlocillin was conjugated with AgNPs by chemical methods and its antimicrobial activity was studied against P. aeruginosa using well diffusion agar method. Then, minimum inhibitory concentration and minimum bactericidal concentration of the new conjugate was specified with macro‐dilution method. The animal study showed the considerable enhanced antibacterial effect of azlocillin in conjugation with AgNPs against P. aeruginosa in comparison with azlocillin alone, AgNPs alone and azlocillin in combination with AgNPs.Inspec keywords: antibacterial activity, silver, nanoparticles, organic compounds, microorganisms, drugs, nanomedicine, biomedical materials, diseases, diffusion, nanofabricationOther keywords: Ag, macrodilution method, minimum bactericidal concentration, minimum inhibitory concentration, well diffusion agar method, P. aeruginosa, antimicrobial activity, chemical methods, azlocillin antibiotic nanoparticles, infectious diseases treatment, nanodrugs, bacterial resistance, Pseudomonas aeruginosa, silver nanoparticles, antibacterial effect相似文献
Sustainable development is currently being applied in most fields of research. Procurement, focused on the buyer–supplier dyad, is one such discipline where sustainability is being widely applied. This paper provides a review of these research studies, conducting a systematic content analysis in order to present the state of the art in this domain. The paper carries out a detailed review of articles in international scientific journals and well-known international conferences related to green and sustainable supplier selection published between 2008 and 2014 inclusive. Seven designed research questions are proposed and answered based on this bibliography. Interesting results are reported in each section and gaps in the current body of literature are identified. The purpose of this review is to provide important future directions and limitations in this research topic. 相似文献