基于终端滑模机器人模糊自适应路径跟踪控制

对质心位置未知的移动机器人系统设计了基于快速终端滑模的模糊自适应路径跟踪控制方法。该方法采用模糊逻辑系统逼近控制器中的未知函数,基于李亚普诺夫稳定性分析方法对未知参数设计自适应律,并设计鲁棒控制器来补偿逼近误差。该方法不但可以保证闭环系统中的所有信号有界,而且可使跟踪误差在有限时间内收敛到原点的小邻域内。仿真结果验证了方法的有效性。     

高阶耦合机器人的自适应模糊滑模分散控制

针对一类存在模型不确定性和未知非线性扰动的机器人系统,考虑其不确定项和未知扰动项的上界是关于系统状态的普通高阶多项式,结合模糊系统的逼近能力,提出了一种基于滑模控制原理的自适应模糊分散控制方法.该方法不仅能够使得关节之间相互耦合的机器人各关节的控制器仅由本关节的信息就能完全确定,而且消除了现存文献在设计机器人分散控制器...     

基于模糊逻辑系统的输出跟踪控制问题

针对一类未知的非线性互联大系统，设计间接自适应模糊控制器以实现跟踪控制，采用模糊控制，模糊逻辑逼近和模糊滑模控制相结合的方法，对维数较低的子系统未知动态和维数较高的互联项未知动态分别采用两类模糊规则进行逼近，对系统的外部干扰及模糊逼近误差采用模糊滑模控制予以抵消，基于Lyapunov方法实现模糊系统中的参数自适应律并在线调节，所设计的间接自适应控制器使系统在Lyapunov意义下稳定，且跟踪误差趋近于0，仿真结果表明了该设计方法的正确性。     

线控转向系统的自适应高阶滑模控制

车辆线控转向(steer-by-wire,SbW)系统存在摩擦力矩及回正力矩等不确定动态特性,难以实现精确建模与有效控制.为此,提出一种基于自适应模糊逻辑系统的自适应高阶滑模(adaptive higher-order sliding mode, AHOSM)方法,实现SbW系统的有效控制.首先,通过自适应模糊逻辑系统逼近SbW系统的未知动态,使控制器的设计不再需要摩擦力矩及回正力矩的动力学模型;其次,采用高阶滑模和自适应增益技术削弱传统滑模控制器存在的抖振现象;再次,通过构造Lyapunov函数设计增益自适应律补偿逼近误差和系统不确定项对控制精度的影响,该方案不需要系统不确定项的界已知,且能够避免增益过估计现象;最后,通过稳定性分析证明该控制器可以在有限时间内建立实际滑动模态,数字仿真和硬件在环实验进一步验证了该控制方法的有效性和优越性.     

基于函数滑模控制器的机械手轨迹跟踪控制

提出一种基于函数滑模控制器(FSMC)的控制策略,用于不确定机械手的轨迹跟踪控制。首先,由动力学模型和滑模函数得到系统的不确定项;然后,利用RBF神经网络逼近系统不确定项,由于神经网络逼近存在误差,而且在初始阶段误差较大,设计函数滑模控制器和鲁棒补偿项对神经网络逼近误差进行补偿,以克服普通滑模控制器容易引起的抖振问题,同时提高系统的跟踪控制性能。基于李亚普诺夫理论证明了闭环系统的全局稳定性,仿真实验也验证了方法的有效性。     

基于函数滑模控制器的机械手轨迹跟踪控制

提出一种基于函数滑模控制器(FSMC)的控制策略,用于不确定机械手的轨迹跟踪控制。首先,由动力学模型和滑模函数得到系统的不确定项;然后,利用RBF神经网络逼近系统不确定项,由于神经网络逼近存在误差,而且在初始阶段误差较大,设计函数滑模控制器和鲁棒补偿项对神经网络逼近误差进行补偿,以克服普通滑模控制器容易引起的抖振问题,同时提高系统的跟踪控制性能。基于李亚普诺夫理论证明了闭环系统的全局稳定性,仿真实验也验证了方法的有效性。     

基于LuGre 摩擦模型的机械臂模糊神经网络控制

针对未知摩擦非线性会使机械臂控制精度难以提高的缺陷,建立基于动态LuGre摩擦的机械臂模型.在系统参数未知和机械臂负载变化的情况下,设计一种自适应模糊神经网络控制器,采用基函数中心和宽度均自适应变化的模糊神经网络补偿器,实现对系统中包括LuGre摩擦在内的非线性环节的逼近,并利用滑模控制项减小逼近误差.通过Lyapunov方法证明了闭环系统的稳定性,并通过仿真结果验证了所提出控制方法的有效性.     

基于RBF神经网络的多关节机器人固定时间滑模控制

针对具有典型非线性特性的多关节机器人轨迹跟踪控制问题,提出一种基于径向基函数(RBF)神经网络的固定时间滑模控制方法.首先,基于凯恩方法建立包括系统模型不确定性以及外部干扰在内的多关节机器人动力学模型;然后,根据机器人动力学模型设计一种固定时间收敛的滑模控制器, RBF神经网络用来逼近系统模型中的不确定性项,并利用Lyapunov理论证明该系统跟踪误差能在固定时间内收敛;最后,对特定型号的多关节机器人虚拟样机进行仿真分析,结果表明:与基于RBF神经网络的有限时间滑模控制器相比,所提出控制器具有良好的跟踪性能且能保证系统状态在固定时间内收敛.     

机器人操作器的自适应模糊滑模控制器设计

针对机器人动力学系统提出了一种基于模糊逻辑的自适应模糊滑模控制方案.根据滑模控制原理并利用模糊系统的逼近能力设计控制器,基于李雅谱诺夫方法设计自适应律,证明了闭环模糊控制系统的稳定性和跟踪误差的收敛性.控制结构简单,不需要复杂的运算.该设计方案柔化了控制信号,减轻了一般滑模控制的抖振现象.仿真结果表明了所提控制策略的有效性.     

神经网络自适应滑模控制的不确定机器人轨迹跟踪控制

提出一种针对机器人跟踪控制的神经网络自适应滑模控制策略。该控制方案将神经网络的非线性映射能力与滑模变结构和自适应控制相结合。对于机器人中不确定项,通过RBF网络分别进行自适应补偿,并通过滑模变结构控制器和自适应控制器消除逼近误差。同时基于Lyapunov理论保证机器手轨迹跟踪误差渐进收敛于零。仿真结果表明了该方法的优越性和有效性。     

Only connect: teaching, technology and telesis

Abstract This paper describes an approach to the design of interactive multimedia materials being developed in a European Community project. The developmental process is seen as a dialogue between technologists and teachers. This dialogue is often problematic because of the differences in training, experience and culture between them. Conditions needed for fruitful dialogue are described and the generic model for learning design used in the project is explained.     

European Community policy and the market

Abstract This paper starts with some reflections on the policy considerations and priorities which are shaping European Commission (EC) research programmes. Then it attempts to position the current projects which seek to capitalise on information and communications technologies for learning in relation to these priorities and the apparent realities of the marketplace. It concludes that while there are grounds to be optimistic about the contribution EC programmes can make to the efficiency and standard of education and training, they are still too technology driven.     

一种自适应子融合集成多分类器方法

融合集成方法已经广泛应用在模式识别领域,然而一些基分类器实时性能稳定性较差,导致多分类器融合性能差,针对上述问题本文提出了一种新的基于多分类器的子融合集成分类器系统。该方法考虑在度量层融合层次之上通过对各类基多分类器进行动态选择,票数最多的类别作为融合系统中对特征向量识别的类别,构成一种新的自适应子融合集成分类器方法。实验表明,该方法比传统的分类器以及分类融合方法识别准确率明显更高,具有更好的鲁棒性。     

Avoiding semantic and temporal gaps in developing software intensive systems

Development of software intensive systems (systems) in practice involves a series of self-contained phases for the lifecycle of a system. Semantic and temporal gaps, which occur among phases and among developer disciplines within and across phases, hinder the ongoing development of a system because of the interdependencies among phases and among disciplines. Such gaps are magnified among systems that are developed at different times by different development teams, which may limit reuse of artifacts of systems development and interoperability among the systems. This article discusses such gaps and a systems development process for avoiding them.     

Designing economic np control charts: A programmed simulation approach

This paper presents control charts models and the necessary simulation software for the location of economic values of the control parameters. The simulation program is written in FORTRAN, requires only 10K of main storage, and can run on most mini and micro computers. Two models are presented - one describes the process when it is operating at full capacity and the other when the process is operating under capacity. The models allow the product quality to deteriorate to a further level before an existing out-of-control state is detected, and they can also be used in situations where no prior knowledge exists of the out-of-control causes and the resulting proportion defectives.     

The development of robot art

Going through a few examples of robot artists who are recognized worldwide, we try to analyze the deepest meaning of what is called “robot art” and the related art field definition. We also try to highlight its well-marked borders, such as kinetic sculptures, kinetic art, cyber art, and cyberpunk. A brief excursion into the importance of the context, the message, and its semiotics is also provided, case by case, together with a few hints on the history of this discipline in the light of an artistic perspective. Therefore, the aim of this article is to try to summarize the main characteristics that might classify robot art as a unique and innovative discipline, and to track down some of the principles by which a robotic artifact can or cannot be considered an art piece in terms of social, cultural, and strictly artistic interest. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Explanation and prediction: an architecture for default and abductive reasoning

Although there are many arguments that logic is an appropriate tool for artificial intelligence, there has been a perceived problem with the monotonicity of classical logic. This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of our assumptions. The two activities of predicting what is expected to be true and explaining observations are considered in a simple theory formation framework. Properties of each activity are discussed, along with a number of proposals as to what should be predicted or accepted as reasonable explanations. An architecture is proposed to combine explanation and prediction into one coherent framework. Algorithms used to implement the system as well as examples from a running implementation are given.     

Three Process Perspectives: Organizations, Teams, and People

This paper provides the author's personal views and perspectives on software process improvement. Starting with his first work on technology assessment in IBM over 20 years ago, Watts Humphrey describes the process improvement work he has been directly involved in. This includes the development of the early process assessment methods, the original design of the CMM, and the introduction of the Personal Software Process (PSP)^SM and Team Software Process (TSP){^SM}. In addition to describing the original motivation for this work, the author also reviews many of the problems he and his associates encountered and why they solved them the way they did. He also comments on the outstanding issues and likely directions for future work. Finally, this work has built on the experiences and contributions of many people. Mr. Humphrey only describes work that he was personally involved in and he names many of the key contributors. However, so many people have been involved in this work that a full list of the important participants would be impractical.     

基于复小波噪声方差显著修正的SAR图像去噪

提出了一种基于复小波域统计建模与噪声方差估计显著性修正相结合的合成孔径雷达(Synthetic Aperture Radar,SAR)图像斑点噪声滤波方法。该方法首先通过对数变换将乘性噪声模型转化为加性噪声模型,然后对变换后的图像进行双树复小波变换(Dualtree Complex Wavelet Transform,DCWT),并对复数小波系数的统计分布进行建模。在此先验分布的基础上,通过运用贝叶斯估计方法从含噪系数中恢复原始系数,达到滤除噪声的目的。实验结果表明该方法在去除噪声的同时保留了图像的细节信息,取得了很好的降噪效果。     

How do children do mathematics with LOGO?

Abstract  This paper considers some results of a study designed to investigate the kinds of mathematical activity undertaken by children (aged between 8 and 11) as they learned to program in LOGO. A model of learning modes is proposed, which attempts to describe the ways in which children used and acquired understanding of the programming/mathematical concepts involved. The remainder of the paper is concerned with discussing the validity and limitations of the model, and its implications for further research and curriculum development.