Robust neural network tracking controller using simultaneous perturbation stochastic approximation

This paper considers the design of robust neural network tracking controllers for nonlinear systems. The neural network is used in the closed-loop system to estimate the nonlinear system function. We introduce the conic sector theory to establish a robust neural control system, with guaranteed boundedness for both the input/output (I/O) signals and the weights of the neural network. The neural network is trained by the simultaneous perturbation stochastic approximation (SPSA) method instead of the standard backpropagation (BP) algorithm. The proposed neural control system guarantees closed-loop stability of the estimation system, and a good tracking performance. The performance improvement of the proposed system over existing systems can be quantified in terms of preventing weight shifts, fast convergence, and robustness against system disturbance.     

A novel generic hebbian ordering-based fuzzy rule base reduction approach to mamdani neuro-fuzzy system

There are two important issues in neuro-fuzzy modeling: (1) interpretability--the ability to describe the behavior of the system in an interpretable way--and (2) accuracy--the ability to approximate the outcome of the system accurately. As these two objectives usually exert contradictory requirements on the neuro-fuzzy model, certain compromise has to be undertaken. This letter proposes a novel rule reduction algorithm, namely, Hebb rule reduction, and an iterative tuning process to balance interpretability and accuracy. The Hebb rule reduction algorithm uses Hebbian ordering, which represents the degree of coverage of the samples by the rule, as an importance measure of each rule to merge the membership functions and hence reduces the number of the rules. Similar membership functions (MFs) are merged by a specified similarity measure in an order of Hebbian importance, and the resultant equivalent rules are deleted from the rule base. The rule with a higher Hebbian importance will be retained among a set of rules. The MFs are tuned through the least mean square (LMS) algorithm to reduce the modeling error. The tuning of the MFs and the reduction of the rules proceed iteratively to achieve a balance between interpretability and accuracy. Three published data sets by Nakanishi (Nakanishi, Turksen, & Sugeno, 1993), the Pat synthetic data set (Pal, Mitra, & Mitra, 2003), and the traffic flow density prediction data set are used as benchmarks to demonstrate the effectiveness of the proposed method. Good interpretability, as well as high modeling accuracy, are derivable simultaneously and are suitably benchmarked against other well-established neuro-fuzzy models.     

Discrete J-spectral factorization

This paper deals with the J-spectral factorization for general discrete rational matrices. A simple approach based on the Kalman filtering in Krein space is proposed. The main idea is to construct a stochastic state space filtering model in Krein space such that the spectral matrix of the output is equal to the rational matrix to be factorized. The spectral factor is then easily derived by using the generalized Kalman filtering in Krein space, which is similar to the H₂ spectral factorization. Our approach unifies the treatment of the H₂ spectral factorization and the J-spectral factorization. The applications of the derived results in H_∞ and risk-sensitive estimation for both nonsingular and singular systems are demonstrated.     

Deformation and failure of adhesive bonds under shear loading

Experiments have shown that certain mechanical properties can be greatly enhanced when a material is stressed while under tight spatial constraint. In this work, the post-yield behaviour of brittle and ductile epoxy resins used as thin adhesive bonds was determined using the napkin ring shear test. Real-time observations of the deformation in the bond as well as SEM post-failure analysis were employed to gain information on the failure process. The complete stress-strain histories of the adhesives were established for bond thicknesses ranging from the micrometre level up to values large enough to expose the bulk properties. The most dramatic variations occurred for the ultimate shear strain, _f; for the brittle adhesive, _f increased by over 30-fold relative to the bulk material when the bond thickness, t, was decreased to a few micrometres. Experimental evidence and analytical considerations suggest that the decline of _f with t was due to premature bond failure caused by tensile microcracks or voids that were formed in the interlayer during loading, with the specific _f versus t relationship being a mere reflection of the variations in the degree of stress concentration at the tip of the flaws. The astonishingly large value of _f (i.e. 2.8–3.4) found for the brittle epoxy in the micrometre thickness range, is believed to represent the intrinsic shear strain of this material.     

Observation of deformation and damage at the tip of cracks in adhesive bonds loaded in shear and assessment of a criterion for fracture

The evolution of damage at the tip of cracks in adhesive bonds deforming in shear was monitored in real time using a high-magnification video camera. Brittle and a ductile epoxy resins were evaluated, with the bond thickness t being an experimental variable. An extensive zone of plastic deformation developed ahead of the crack tip prior to fracture. In the case of the brittle adhesive, for relatively thick bonds tensile microcracks formed within that zone. Increased loading caused the microcracks to grow from the interlayer to the interface, which led to a complete bond separation after interface cracks emanating from adjacent microcracks linked. In contrast, for the ductile adhesive the crack always grew from the tip. Strain gradients tended to develop there when the bond thickness was large.The adhesive shear strain was determined from fine lines scratched on the specimen edge. For both adhesives, the average crack tip shear strain at crack propagation rapidly decreased with increasing t. This effect was attributed to the changing sensitivity of the bond to the presence of flaws; thicker bonds can accommodate larger microcracks or microvoids which cause greater stress concentration. For a given bond thickness, the critical crack tip shear strain agreed well with the ultimate shear strain of the unflawed adhesive previously determined using the napkin ring shear test [12]. This suggests that the ultimate shear strain is a key material property controlling crack growth. The critical distortional strain energy/unit area of the unflawed adhesive W _s was determined from the area under the stress-strain curve in the napkin ring test. Good agreement between W _s and the adhesive mode II fracture energy was found for all joints tested except for relatively thick bonds. For the particular case of an elastic-perfectly plastic adhesive, the agreement above implies % MathType!MTEF!2!1!+-% feaafiart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGak0dh9WrFfpC0xh9vqqj-hEeeu0xXdbba9frFj0-OqFf% ea0dXdd9vqaq-JfrVkFHe9pgea0dXdar-Jb9hs0dXdbPYxe9vr0-vr% 0-vqpWqaaeaabaGaciaacaqabeaadaqaaqaaaOqaaGqaciaa-Deada% WgaaWcbaacbaGaa4xsaiaa+LeacaGFdbaabeaakiabg2da9iaa-Dfa% daWgaaWcbaGaa83CaaqabaGccqGHHjIUcaWF0bGaeqiXdq3aaSbaaS% qaaiaa-LhaaeqaaOGaeq4SdC2aaSbaaSqaaiaa-zgaaeqaaaaa!463A!\[G_{IIC} = W_s \equiv t\tau _y \gamma _f \].     

Improved MCMAC with momentum, neighborhood, and averagedtrapezoidal output

An improved modified cerebellar articulation controller (MCMAC) neural control algorithm with better learning and recall processes using momentum, neighborhood learning, and averaged trapezoidal output, is proposed in this paper. The learning and recall processes of MCMAC are investigated using the characteristic surface of MCMAC and the control action exerted in controlling a continuously variable transmission (CVT). Extensive experimental results demonstrate a significant improvement with reduced training time and an extended range of trained MCMAC cells. The improvement in recall process using the averaged trapezoidal output (MCMAC-ATO) are contrasted against the original MCMAC using the square of the Pearson product moment correlation coefficient. Experimental results show that the new recall process has significantly reduced the fluctuations in the control action of the MCMAC and addressed partially the problem associated with the resolution of the MCMAC memory array.     

基于数字电路系统的高速PCB信号完整性分析

信号缺失、信号串扰等问题要求电路板设计初期考虑信号完整性.为此,基于高速通用信号处理平台在设计中所遇到的信号完整性的阻抗匹配问题进行探讨,并对阻抗匹配进行仿真,通过调整端接匹配电阻,得出优化结果.结果表明,实验结果与实际情况相符合.     

Web服务认证技术综述

Web服务为代表的软件服务及服务协同成为互联网应用的主流,针对Web服务认证是Web服务访问控制和安全调用的前提,分析传统认证机制在满足Web服务对跨域认证需求方面所存在的缺陷,归纳和分类了当前Web服务认证技术的研究成果,论述Web服务安全标准WS-Security、基于声明标记语言SAML和基于XML加密管理规范XKMS的服务认证技术,最后讨论了Web服务认证技术的挑战和研究趋势。     

面向机器自动识别的方位词“中”的用法规则研究

构建面向机器的现代汉语方位词知识库(方位词用法机器词典、方位词用法规则库),对于现代汉语方位词用法的自动识别研究具有重要的意义。致力于面向机器的方位词"中"的用法自动识别研究,以《人民日报》2000年1月-6月的语料作为实验数据,通过对其原始规则的自动识别结果的分析,调整和改进了面向机器识别的方位词"中"的规则描述,把方位词"中"的用法识别准确率由12.88%提高到86.35%,使现代汉语方位词用法规则库得到了进一步完善。     

基于Matlab GUI的数字滤波器设计及其应用

基于数字信号处理原理,在分析数字滤波器设计理论和Matlab编程技术及其GUI图形用户界面设计的基础上,开发了具有交互式特点的数字滤波器软件,界面操作简单方便,可以根据需要选择滤波器类型,输入相关参数,然后选择相应的功能按钮,就可以得到滤波器的特性参数,并进行滤波器的性能分析,打破了以往滤波器设计过程中大量繁琐的数值计算问题,为数字滤波器的设计和应用提供了一个有效的辅助工具。