多分支平行双线输电线故障定位算法的研究

本文针对多分支平行双线输电线提出了一种新的故障定位方法。应用相同的算法对全部分支进行逐条搜索,故障分支和故障点位置可以一并被确定。经仿真证明,该方法是有效的。     

PWM逆变器的一种神经网络控制方法

提出一种用于ＰＷＭ逆变器控制的神经网络控制器、通过仿真和实验研究表明,这种基于动态ＢＰ神经网络的控制器可以使逆变器获得较好的动、静态特性、并且对电源、负载扰动有较强的适应能力。     

Dependence of giant magnetoresistance on microstructures in ion-beam co-sputtered CoxAg1−x granular films

A number of structural analysis methods were employed to investigate the microstructures of ion-beam co-sputtering of Co _x Ag_1–x (0x100 at%) granular films. Forx=22 at%, the sample which has the optimal giant magnetoresistance at room temperature, there exists either crystallized or highly disordered regions shown by high-resolution electron microscopy. At the boundary between cobalt granules and the silver matrix, lattice mismatch was formed, leading to roughness of the interfaces. X-ray diffraction and transmission electron microscopy revealed that the samples had f c c structure at lowx, with (111) texture, and the h c p structure gradually appeared as x>75 at %. Relative lattice expansion was observed asx increased.     

智能CAI软件生成平台

本文概要介绍“智能ＣＡＩ软件生成平台”的研制目标,设计思想,主要功能和技术特点及其实现。     

Fabrication of large-volume microfluidic chamber embedded in glass using three-dimensional femtosecond laser micromachining

We report on fabrication of large-volume, square-shaped microfluidic chamber embedded in glass by scanning a tightly focused femtosecond laser beam inside a porous glass immersed in water. After the hollow structure is created in the porous glass substrate, the fabricated glass sample is post-annealed at 1,050°C during which it can be sintered into a compact glass. By the use of this technique, a 1 mm × 1 mm × 100 μm microchamber connected to four microfluidic channels is created inside the transparent glass substrate, showing that our technique allows for fabrication of not only thin channel structures with arbitrary lengths and configurations, but also hollow structures with infinitely large sizes.     

Modeling and Neuro-Fuzzy adaptive attitude control for Eight-Rotor MAV

This paper focuses on modeling and intelligent control of the new Eight-Rotor MAV which is used to solve the problem of low coefficient proportion between lift and gravity for Quadrotor MAV. The dynamical and kinematical modeling for the Eight-Rotor MAV was developed which has never been proposed before. Based on the achieved dynamic modeling, two types of controller were presented. One type, a PID controller is derived in a conventional way with simplified dynamics and turns out to be quite sensitive to sensor noise as well as external perturbation. The second type controller is the Neuro-Fuzzy adaptive controller which is composed of two type-II fuzzy neural networks (TIIFNNs) and one PD controller: The PD controller is adopted to control the attitude, one of the TIIFNNs is designed to learn the inverse model of Eight-Rotor MAV on-line, the other one is the copy of the former one to compensate for model errors and external disturbances, both structure and parameters of T-IIFNNs are tuned on-line at the same time, and then the stability of the Eight-Rotor MAV closed-loop control system is proved using Lyapunov stability theory. Finally, the validity of the proposed control method has been verified through real-time experiments. The experimental results show that the performance of Neuro-Fuzzy adaptive controller performs very well under sensor noise and external disturbances, and has more superiority than traditional PID controller.     

An LMI Approach to consensus in second-order multi-agent systems

This paper deals with the consensus problem of the second-order multi-agent systems based on linear system theory. By a system transformation, the consensus problem is converted to the stability problem of a linear system. The second-order systems considered include the systems with both the fixed topology and the Markov switching topology. Necessary and sufficient conditions of consensus or mean square consensus are obtained. The results are extended to the cases of the uncertain transition probability rates and time-delay, respectively. Finally, a simulation example is given to show the effectiveness of the presented results.     

Ensemble of surrogates with recursive arithmetic average

Surrogate models are often used to replace expensive simulations of engineering problems. The common approach is to construct a series of metamodels based on a training set, and then, from these surrogates, pick out the best one with the highest accuracy as an approximation of the computationally intensive simulation. However, because the choice of approximate model depends on design of experiments (DOEs), the traditional strategy thus increases the risk of adopting an inappropriate model. Furthermore, in the design of complex product system, because of its feature of one-of-a-kind production, acquiring more samples is very expensive and intensively time-consuming, and sometimes even impossible. Therefore, in order to save sampling cost, it is a reasonable strategy to take full advantage of all the stand-alone surrogates and then combine them into an ensemble model. Ensemble technique is an effective way to make up for the shortfalls of traditional strategy. Motivated by the previous research on ensemble of surrogates, a new technique for constructing of a more accurate ensemble of surrogates is proposed in this paper. The weights are obtained using a recursive process, in which the values of these weights are updated in each iteration until the last ensemble achieves a desirable prediction accuracy. This technique has been evaluated using five benchmark problems and one reality problem. The results show that the proposed ensemble of surrogates with recursive arithmetic average provides more ideal prediction accuracy than the stand-alone surrogates and for most problems even exceeds the previously presented ensemble techniques. Finally, we should point out that the advantages of combination over selection are still difficult to illuminate. We are still using an “insurance policy” mode rather than offering significant improvements.     

Fast structural optimization with frequency constraints by genetic algorithm using adaptive eigenvalue reanalysis methods

Structural optimization with frequency constraints is highly nonlinear dynamic optimization problems. Genetic algorithm (GA) has greater advantage in global optimization for nonlinear problem than optimality criteria and mathematical programming methods, but it needs more computational time and numerous eigenvalue reanalysis. To speed up the design process, an adaptive eigenvalue reanalysis method for GA-based structural optimization is presented. This reanalysis technique is derived primarily on the Kirsch’s combined approximations method, which is also highly accurate for case of repeated eigenvalues problem. The required number of basis vectors at every generation is adaptively determined and the rules for selecting initial number of basis vectors are given. Numerical examples of truss design are presented to validate the reanalysis-based frequency optimization. The results demonstrate that the adaptive eigenvalue reanalysis affects very slightly the accuracy of the optimal solutions and significantly reduces the computational time involved in the design process of large-scale structures.     

Potentials of IR-UWB technology for ubiquitous computing

Connectivity is very important to enable ubiquitous computing. Wireless communication plays a continual key role in future ubiquitous network where all devices need to be connected freely. Ultra-wideband (UWB) radio is a new method of short-range wireless technology which is suit for ubiquitous computing. In this paper, we provided the potentials of impulse radio UWB (IR-UWB) technology in ubiquitous computing environments. Our study investigated possible communication methods which can be used in ubiquitous network. Comparisons between different communication technologies demonstrated that UWB-based solutions can support identification, location, sensing, and connectivity. In addition, we proposed two typical schemes which show how IR-UWB is used in ubiquitous computing.