Intelligent control of doubly‐fed induction generator systems using PIDNNs

An intelligent control for a stand‐alone doubly‐fed induction generator (DFIG) system using a proportional‐integral‐derivative neural network (PIDNN) is proposed in this study. This system can be applied as a stand‐alone power supply system or as the emergency power system when the electricity grid fails for all sub‐synchronous, synchronous, and super‐synchronous conditions. The rotor side converter is controlled using field‐oriented control to produce 3‐phase stator voltages with constant magnitude and frequency at different rotor speeds. Moreover, the grid side converter, which is also controlled using field‐oriented control, is primarily implemented to maintain the magnitude of the DC‐link voltage. Furthermore, the intelligent PIDNN controller is proposed for both the rotor and grid side converters to improve the transient and steady‐state responses of the DFIG system for different operating conditions. Both the network structure and online learning algorithm are introduced in detail. Finally, the feasibility of the proposed control scheme is verified through experimentation. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Hysteresis Compensation and Adaptive Controller Design for a Piezoceramic Actuator System in Atomic Force Microscopy

This paper presents an indirect adaptive controller combined with hysteresis compensation to achieve high accuracy positioning control of piezoceramic actuators and illustrates the results with an atomic force microscope (AFM) application. A dynamic model of a piezoceramic actuator system in AFM is derived and analyzed. A feedforward controller based on the Preisach model is proposed to compensate for the nonlinear hysteresis effects. Then an indirect adaptive controller is designed to achieve desired tracking performance as well as deal with the uncompensated nonlinearity from hysteresis and the system parameter variation due to creep. Experimental results indicate that the proposed controller can significantly improve the positioning control accuracy of the piezoceramic actuator as well as achieve high image quality of the AFM system. The maximum scanning error was reduced from 2µm to 0.3µm in comparison with a proportional‐integral‐derivative (PID) controller. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Adaptive synchronization of the complex dynamical network with double non-delayed and double delayed coupling

To simulate more realistic networks, we introduce a complex dynamical network model with double non-delayed and double delayed coupling and further investigate its synchronization phenomenon in this paper. Based on Lyapunov stability theory, adaptive synchronization criteria is obtained. Analytical result shows that under the designed adaptive controllers, the complex dynamical network with double non-delayed and double delayed coupling can asymptotically synchronize to a given trajectory. What is more, the coupling matrix is not assumed to be symmetric or irreducible. Finally, simulation results show the method is effective.     

Improved stability conditions for systems with interval time-varying delay

The paper is concerned with the stability of linear systems with interval time-varying delay. Through constructing a new augmented Lyapunov-Krasovskii functional (LKF) which contains some quadruple-integral terms and estimating the time derivative of the LKF less conservatively, new stability criteria are derived without introducing any free matrices. Moreover, by proving the positive definiteness of the LKF with some integral inequalities, the constraints on some functional parameters are relaxed and the conservatism of the obtained results are further reduced. Numerical examples are also given to demonstrate the effectiveness and reduced conservatism of the obtained results.     

基于五层十五级遥感数据结构的并行算法研究

针对当前环境与监测预报小卫星宽覆盖和海量数据显示与处理不足的现状,设计五层十五级遥感数据组织结构,并依据此结构设计一种新的并行计算算法,得到并行计算的最大近优估算值,优化环境与监测预报小卫星海量数据的遥感产品生产能力,提高环境监测预报效率。     

基于多权重因子的PageRank算法改进

现有PageRank算法的多种改进研究,对新网页歧视、语言差异歧视、主题漂移、忽视用户浏览兴趣等问题仍然没有给出较好的解决方案。本文提出改进算法TWPR(PageRank based on Three Weights)。该算法将时间特性分析、语言链接结构分析和用户行为相结合,旨在提升更新较快、链接行为优良、用户感兴趣度高的中文网页PR值。实验证明,改进算法可有效提高网页检索的命中率,改善搜索质量。     

基于SOA的高校教学管理平台

通过分析高校教学管理目前信息化面临的问题,提出基于SOA体系结构对目前的应用系统进行整合,实现各应用系统之间的协同工作。描述了教学管理平台的需求、体系结构、设计思路,说明了在开发过程中所使用的关键技术。同时在实现了基于SOA体系结构的教学管理平台之后,在移动终端上开发了相应的客户端应用程序,使学生能够实时了解相关教学信息。     

保持边缘特征和增强对比度的图像缩放算法

图像的边缘信息和对比度是影响人体视觉的最主要因素。提出一种能够同时保持边缘特征和增强对比度的图像缩放新方法。通过边缘检测算法、边缘梯度增强以及梯度图的低通滤波算法,得到新的梯度图,再通过求解泊松方程得到重建的图像。由于对图像边缘作了特殊处理,从而避免在图像缩放过程中丢失边缘信息。该方法可以同时保持特征以及增加图像的对比度,从而更好地展现图像的细节。实验结果表明,本文方法能应用于一般图像和医学图像的缩放和增强等应用中。     

基于改进最大熵算法的煤矿安全监测系统设计

研究了煤矿安全监测及灾害预警的检测问题,提高检测的准确性。已有的煤矿安全监测技术多是基于单层传感网络设计,当瓦斯等危险气氛浓度泄露受到外界干扰,容易发生检测节点特征退化,传统方法抗噪能力差,效率低,监测结果不稳定。为了解决这一问题,提出一种基于改进最大熵算法的井下实时监控与灾害监测预警系统设计方法。设计了基于抗干扰的最大熵检索建模功能,快速计算跳数和能耗信息,实现安全隐患的准确检测。仿真结果表明,系统能够大幅降低干扰风险,取得良好的效果。