多关节机器人的模糊神经滑模控制

针对含有建模误差和不确定干扰的多关节机器人轨迹跟踪控制,提出了一种模糊神经滑模控制方法.该方法采用全局快速终端滑模面,保证了系统能够从任意初始状态在有限时间内到达滑模面和平衡点.采用模糊神经网络自适应地补偿系统的建模误差和外界干扰,保证了滑模控制在滑模面的运动.文中利用李亚普诺夫稳定性判据推导出了控制器的控制律和模糊神经网络的目标函数,通过模糊神经网络的在线学习.削弱了滑模控制的抖振.仿真结果表明了其有效性.     

多关节机器人的神经滑模控制

针对含有建模误差和不确定干扰的多关节机械臂轨迹跟踪控制,提出了一种神经滑模控制方法。该方法采用全局快速终端滑模面保证了系统状态能够在有限时间内到达滑模面和平衡点。采用径向基函数神经网络自适应地补偿系统的建模误差和外界干扰,保证了滑模控制在滑模面的运动。利用李亚普诺夫稳定性判据推导出了控制器的控制律和神经网络的目标函数,通过神经网络的在线学习,削弱了滑模控制的抖振。仿真结果表明了其有效性。     

基于径向基函数神经网络的多关节机器人滑模控制器

针对具有不确定性的多关节机器人系统,提出了一种径向基函数神经滑模控制方法;该控制方案采用全局滑模面,将神经网络的非线性映射能力与滑模控制的特点相结合,利用径向基神经网络自适应学习系统不确定性的未知上界,消弱了由滑模控制产生的抖动,同时保证了系统的鲁棒性;基于李亚普诺夫定理给出了系统稳定性的充分条件;仿真结果表明,该方法具有良好的轨迹跟踪和速度跟踪性能,提高了对于建模误差和不确定干扰等因素的鲁棒性。     

多关节机械臂轨迹跟踪自适应神经网络滑模控制

针对不确定干扰和建模误差对多关节机械臂轨迹跟踪控制系统造成的不良影响,对基于滑模控制的自适应神经网络滑模控制算法进行了研究。通过神经网络,对多关节机械臂轨迹跟踪控制系统的不确定干扰和建模误差进行逼近。添加自适应项,补偿神经网络滑模控制中神经网络模型对系统中的不确定干扰和建模误差的逼近误差。设计了具有指数趋近律的滑模面,以提升多关节机械臂轨迹跟踪控制系统的鲁棒性和响应速度。使用李雅普诺夫稳定性理论,证明了多关节机械臂轨迹跟踪控制系统的半全局稳定性,并通过MATLAB对理论结果进行了仿真验证。仿真结果表明,对具有不确定干扰和建模误差的多关节机械臂轨迹跟踪控制系统,采用该算法进行轨迹跟踪时,具有较好的稳定性与鲁棒性。该控制算法能合理应用到此类轨迹跟踪控制系统中。     

控制增益符号未知的不确定非线性系统鲁棒自适应控制

针对一类控制增益函数及符号均未知的不确定非线性系统,基于反推滑模设计方法,提出一种鲁棒自适应神经网络控制方案.结合Nussbaum增益设计技术和神经网络逼近能力,取消了控制增益函数及符号已知的条件,应用积分型Lyapunov函数避免了控制器奇异性问题,并通过引入神经网络逼近误差和不确定干扰上界的自适应补偿项消除了建模误差和不确定干扰的影响.理论分析证明了闭环系统所有信号半全局一致终结有界,仿真结果验证了该方法的有效性.     

空间微重力环境地面模拟系统的控制器设计

针对小型和迷你型试验目标,提出一种新的空间微重力环境模拟系统.系统采用平面气浮和气缸垂直悬浮组合方案来模拟空间微重力环境,并采用恒张力控制思想来模拟垂直地面方向上的微重力状态.采用RBF神经网络控制和滑模变结构控制复合控制方案,其中RBF神经网络用于逼近和补偿系统的不确定信息,并作为前馈补偿使跟踪误差快速收敛;通过滑模变结构控制消除RBF神经网络的逼近误差和不定随机干扰的影响,保证系统的鲁棒性.实验研究结果表明,该控制方案是有效的,系统具有较好的动态响应能力、鲁棒性和自适应能力.     

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。     

基于滑模控制器的双臂机器人控制仿真

针对工业机械臂运动控制中由于建模误差和未知干扰导致的控制误差问题,基于机器人力矩控制方法,采用滑模控制理论,利用关节角运动误差,设计并搭建机器人控制系统。以安川Motoman-SDA20机器人为例,对该机器人进行了运动学与动力学分析,搭建相关数学模型,并针对该机器人系统设计了滑模运动控制器。在机器人仿真环境VERP与Simulink中搭建联合仿真平台,对虚拟环境中的机械臂进行运动控制仿真试验,验证了算法的有效性。试验对比了逆运动学控制与滑模控制算法效果,同时对滑模控制算法在机械臂定点运动与轨迹跟踪中的控制效果进行了验证与分析。该控制算法计算过程简明、便于设计。利用VERP仿真平台,获得了更加直观的效果,实现了存在较大建模误差与较小控制频率下的机械臂位置控制,角度误差在0. 3 rad以内。该研究对于机器人控制算法的研究与仿真环境的搭建具有借鉴意义。     

机器人轨迹跟踪的自适应模糊神经网络控制

研究机器人跟踪轨迹控制问题,针对模型未知的机器人系统,为提高跟踪精度和控制性能,提出了一种基于T-S型模糊RBF神经网络的H∞轨迹跟踪控制方法,用模糊神经网络为模型未知的机器人系统建模,克服了系统鲁棒性差,对机动目标跟踪性能差等缺点。然后设计自适应控制器,将H∞控制理论与模糊神经网络有机地结合起来,借助鲁棒补偿项将建模误差及外部干扰衰减到期望的程度以下,而控制器与改进Elman神经网络的结合,便于处理建模有界干扰以及非结构化的未建模的动力学,并进行仿真。仿真结果表明了所提出的控制算法的可行性。     

机器人全局PID模糊滑模跟踪控制与仿真研究

为解决机器人跟踪控制过程中采用PID控制算法会出现抖动和误差的问题,提出了一种机器人全局PID模糊滑模跟踪控制算法.通过将PID滑模控制和模糊控制相结合,设计了全局PID模糊滑模控制;基于模糊规则,对滑模控制增益进行自适应调整,从而消除建模误差和干扰,削弱了控制时产生的抖振,在线调整控制器参数和估计误差,并通过积分来消除外界干扰,因此提高了控制精度.仿真结果表明,与常规的PID算法相比,该方法在处理控制抖动和消除误差以及干扰方面具有极高的鲁棒性.     

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.