Neural network-based sliding mode adaptive control for robot manipulators

This paper addresses the robust trajectory tracking problem for a robot manipulator in the presence of uncertainties and disturbances. First, a neural network-based sliding mode adaptive control (NNSMAC), which is a combination of sliding mode technique, neural network (NN) approximation and adaptive technique, is designed to ensure trajectory tracking by the robot manipulator. It is shown using the Lyapunov theory that the tracking error asymptotically converge to zero. However, the assumption on the availability of the robot manipulator dynamics is not always practical. So, an NN-based adaptive observer is designed to estimate the velocities of the links. Next, based on the observer, a neural network-based sliding mode adaptive output feedback control (NNSMAOFC) is designed. Then it is shown by the Lyapunov theory that the trajectory tracking errors, the observer estimation errors asymptotically converge to zero. The effectiveness of the designed NNSMAC, the NN-based adaptive observer and the NNSMAOFC is illustrated by simulations.     

H∞ filtering of networked discrete-time systems with random packet losses

This paper studies the H_∞ filtering problem for networked discrete-time systems with random packet losses. The general multiple-input-multiple-output (MIMO) filtering system is considered. The multiple measurements are transmitted to the remote filter via distinct communication channels, and each measurement loss process is described by a two-state Markov chain. Both the mode-independent and the mode-dependent filters are considered, and the resulting filtering error system is modelled as a discrete-time Markovian system with multiple modes. A necessary and sufficient condition is derived for the filtering error system to be mean-square exponentially stable and achieve a prescribed H_∞ noise attenuation performance. The obtained condition implicitly establishes a relation between the packet loss probability and two parameters, namely, the exponential decay rate of the filtering error system and the H_∞ noise attenuation level. A convex optimization problem is formulated to design the desired filters with minimized H_∞ noise attenuation level bound. Finally, an illustrative example is given to show the effectiveness of the proposed results.     

A new process for fabricating tip-shaped polymer microstructure array with patterned metallic coatings

In this paper, we present a new process for fabricating tip-shaped polymer microstructure array coated by patterned metal layer. This new process involves three techniques including: micro-molding, patterned metal layer transfer, and electrochemical-based sacrificial layer. As we know, it is very difficult to remove the extra photoresist (PR) in the concave areas in traditional micro-fabrication technology, which hinders patterning metal layers on three-dimensional (3D) microstructures. The electrochemical-based sacrificial layer technique can effectively resolve this problem, which is verified by scanning electron microscopy (SEM) characterization. Comparative study between the 3D metal-coated polyimide microstructures fabricated with and without the electrochemical-based sacrificial layer step is also performed and SEM images proved the effect of the presented process. The applicability of the developed process is also demonstrated with the successful fabrication of a pyramid-shaped polyimide microelectrodes array for neural stimulation.     

Towards capacity and profit optimization of video-on-demand services in a peer-assisted IPTV platform

This paper studies the conditions under which peer-to-peer (P2P) technology may be beneficial in providing IPTV services over typical network architectures. It has three major contributions. First, we contrast two network models used to study the performance of such a system: a commonly used logical “Internet as a cloud” model and a “physical” model that reflects the characteristics of the underlying network. Specifically, we show that the cloud model overlooks important architectural aspects of the network and may drastically overstate the benefits of P2P technology. Second, we propose an algorithm called Zebra that pre-stripes content across multiple peers during idle hours to speed up P2P content delivery in an IPTV environment with limited upload bandwidth. We also perform simulations to measure Zebra’s effectiveness at reducing load on the content server during peak hours. Third, we provide a cost-benefit analysis of P2P video content delivery, focusing on the profit trade-offs for different pricing/incentive models rather than purely on capacity maximization. In particular, we find that under high volume of video demand, a P2P built-in incentive model performs better than any other model, while the conventional no-P2P model generates more profits when the request rate is low. The flat-reward model generally falls in between the usage-based model and the built-in model in terms of profitability except for low request rates. We also find that built-in and flat-reward models are more profitable than the usage-based model for a wide range of subscriber community sizes. Funding for J. Rahe’s research has been provided by AT&T Labs, the State of California under the MICR Oprogram, and by the Toshiba Corporation. Zhen Xiao is partially supported by China MOST project (2006BAH02A10).     

Self-localization and obstacle avoidance for a mobile robot

This article presents a fast self-localization method based on ZigBee wireless sensor network and laser sensor, an obstacle avoidance algorithm based on ultrasonic sensors for a mobile robot. The positioning system and positioning theory of ZigBee which can obtain a rough global localization of the mobile robot are introduced. To realize accurate local positioning, a laser sensor is used to extract the features from environment, then the environmental features and global reference map can be matched. From the matched environmental features, the position and orientation of the mobile robot can be obtained. To enable the mobile robot to avoid obstacle in real-time, a heuristic fuzzy neural network is developed by using heuristic fuzzy rules and the Kohonen clustering network. The experiment results show the effectiveness of the proposed method.     

一种基于接口匹配的组合Web服务描述语言

从基于WSDL的服务接口描述语言入手,分析了Web服务组合的类型和消息依赖关系.将服务组合分为顺序组合、替换组合、混合式组合三种类型;结合这些类型,将组合服务中的消息依赖定义为消息映射依赖、消息合成依赖和消息分解依赖三种关系.在此基础上,提出了一种轻量级的组合服务描述语言(CWSDL).     

Estimating clear-sky land surface longwave upwelling radiation from MODIS data using a hybrid method

Surface longwave upwelling radiation (LWUP) is one of the four components for calculating the earth’s surface radiation budget. Under the general framework of the hybrid method, we developed linear models for estimating the global 1-km instantaneous clear-sky LWUP from the top-of-atmosphere (TOA) radiance of the Moderate Resolution Imaging Spectroradiometer (MODIS) thermal infrared channels 29, 31, and 32. Extensive radiative transfer simulations were conducted to produce a large number of representative samples, from which the linear model was derived. The derived hybrid model was first evaluated using ground measurements collected at 15 sites from two networks (SURFRAD and ASRCOP). According to the validation results, the average bias and root mean square error (RMSE) of ?0.55 and 15.76 W m^?2, respectively, were obtained by averaging the mean bias and RMSE for the two networks. Compared to a hybrid method developed by a previous study and the temperature-emissivity method, our linear model had a superior performance.     

Structure‐adaptive Shape Editing for Man‐made Objects

One of the challenging problems for shape editing is to adapt shapes with diversified structures for various editing needs. In this paper we introduce a shape editing approach that automatically adapts the structure of a shape being edited with respect to user inputs. Given a category of shapes, our approach first classifies them into groups based on the constituent parts. The group‐sensitive priors, including both inter‐group and intra‐group priors, are then learned through statistical structure analysis and multivariate regression. By using these priors, the inherent characteristics and typical variations of shape structures can be well captured. Based on such group‐sensitive priors, we propose a framework for real‐time shape editing, which adapts the structure of shape to continuous user editing operations. Experimental results show that the proposed approach is capable of both structure‐preserving and structure‐varying shape editing.     

The simulation and visual test contact process of a MEMS inertial switch with flexible electrodes

A MEMS inertial switch with flexible electrodes to contact-enhanced is designed and fabricated. ANSYS software is used to simulate the displacement of the mass, deformation of the flexible electrode and contact time of the switch. A high-speed video measurement has been used to visualize the switch contact process instead of electrical measurement for a deeper understanding of the dynamic contact process, and these images are used to visually validate simulation results. Comparisons between the simulation and image results are discussed. The image results are seen to be in good agreement with the dynamics simulation results.     

COS和H_2S毒化F-T合成催化剂热力学分析

利用热力学基础数据和相关软件对F-T合成催化剂COS和H_2S中毒的热力学进行了计算。在热力学上,Ru、Fe、Co的COS中毒在F-T合成反应可以发生的条件下均是自发过程。F-T合成反应体系中10~(-9)级的COS即可使Ru基催化剂中的金属Ru生成RuS_2而中毒。Fe和Co毒化后生成的硫化物种类较多,对这些反应的热力学计算结果表明,对于不同的反应,其平衡常数的差异很大,对应中毒反应发生时,所需的COS和H_2S的浓度也不同,对COS的要求更为严格。由于Fe基F-T合成催化剂活性相的复杂性,利用对催化剂相关性质的修饰开发具有一定抗硫性的铁基F-T合成催化剂是可行的;对于Co催化剂,利用F-T合成的反应特点和催化剂改性开发具有一定抗硫性催化剂是可能的。