Adaptive recurrent neural network control of uncertain constrained nonholonomic mobile manipulators

In this article, motion/force control problem of a class of constrained mobile manipulators with unknown dynamics is considered. The system is subject to both holonomic and nonholonomic constraints. An adaptive recurrent neural network controller is proposed to deal with the unmodelled system dynamics. The proposed control strategy guarantees that the system motion asymptotically converges to the desired manifold while the constraint force remains bounded. In addition, an adaptive method is proposed to identify the contact surface. Simulation studies are carried out to verify the validation of the proposed approach.     

Adaptive training interfaces for less-experienced,elderly users of electronic devices

A great number of complex electronic devices are now part of our everyday lives. While many of us learn to handle these products by trial and error; others, especially older users with little experience in using electronic devices, need support. In order to allow the user maximum flexibility in terms of learning time and location, a training programme is presented which is implemented as part of the software embedded in the product itself. Particular focus is placed on the effect of adaptive training on learning. In this study, the training versions differed in their ability to adjust their complexity to the user's experience (adaptive user interface complexity) and their capability to support the learner by prompting them during the learning process (adaptive training advice). The results show that the adjustment of complexity had a positive effect on users’ experience: elderly users who trained with an adaptive interface were more successful in learning to use a mobile phone. Adaptive training advice, however, was found to have no significant effects on learners’ success and reduced their self-efficacy. This work offers guidelines on how to design integrated training applications for electronic devices that successfully help elderly users with little prior experience.     

A Progressive Deployment Strategy for Cooperative Adaptive Cruise Control to Improve Trafc Dynamics

Cooperative adaptive cruise control(CACC)vehicles are intelligent vehicles that use vehicular ad hoc networks(VANETs)to share trafc information in real time.Previous studies have shown that CACC could have an impact on increasing highway capacities at high market penetration.Since reaching a high CACC market penetration level is not occurring in the near future,this study presents a progressive deployment approach that demonstrates to have a great potential of reducing trafc congestions at low CACC penetration levels.Using a previously developed microscopic trafc simulation model of a freeway with an on-ramp—created to induce perturbations and trigger stop-and-go trafc,the CACC system s efect on the trafc performance is studied.The results show signifcance and indicate the potential of CACC systems to improve trafc characteristics which can be used to reduce trafc congestion.The study shows that the impact of CACC is positive and not only limited to a high market penetration.By giving CACC vehicles priority access to high-occupancy vehicle(HOV)lanes,the highway capacity could be signifcantly improved with a CACC penetration as low as 20%.     

Adaptive tracking control of an autonomous underwater vehicle

This paper presents the trajectory tracking control of an autonomous underwater vehicle(AUV). To cope with parametric uncertainties owing to the hydrodynamic effect, an adaptive control law is developed for the AUV to track the desired trajectory. This desired state-dependent regressor matrix-based controller provides consistent results under hydrodynamic parametric uncertainties.Stability of the developed controller is verified using the Lyapunov s direct method. Numerical simulations are carried out to study the efficacy of the proposed adaptive controller.     

一种用于目标跟踪的波形自适应选择算法

提出了一种用于雷达目标跟踪的自适应广义调频波形设计算法。该算法根据跟踪器的动态需求,以广义调频信号为样板波形自适应设计下一时刻的发射波形,其目的是最小化预测的目标跟踪均方误差,并假定高信噪比条件,且目标跟踪运动模型和观测模型均为线性,利用与某一波形相对应的克拉美--罗下限（CRLB）以及卡尔曼滤波器,通过最小化预测的跟踪均方误差来实现广义调频波形的自适应设计。仿真结果表明：在信噪比相同的情况下,与使用固定参数、自适应参数的线性调频波形设计算法相比,所提出的算法能够获得更低的目标跟踪均方误差。     

基于密度调整的改进自适应谱聚类算法

针对谱聚类存在构造相似度矩阵时对尺度参数敏感以及处理多重尺度数据集效果不理想的缺陷, 提出一种基于密度调整的改进自适应谱聚类算法. 该算法将样本点所处领域的密度引入谱聚类, 利用密度差来调整样本点之间的相似度, 使其更符合实际簇类中样本点间的内在关系, 在一定程度上解决了多尺度聚类问题; 同时, 通过样本点的近邻距离自适应得到尺度参数, 使算法对尺度参数相对不敏感. 仿真实验验证了所提出算法的有效性和优越性.

     

Information systems use as strategy practice: A multi-dimensional view of strategic information system implementation and use

Information systems (IS) are strategic in so far as they are used to realize strategic intent. Yet, while much has been said about aligning IS functionality with the strategic intent and how to organizationally implement strategically aligned systems, less is known of how to successfully implement strategic change associated with system use – a truly critical challenge within strategic IS implementation. Drawing on a strategy-as-practice perspective we address this gap by developing a multi-dimensional view of IS strategy, conceptualizing three key challenges in the IS strategy process, to explain how and why a paper mill, despite successfully implementing a strategic production management system, failed to produce intended strategic change. We call this outcome strategy blindness: organizational incapability to realize the strategic intent of implemented, available system capabilities. Using a longitudinal case study we investigate how cognitive rigidity of key actors and fixed, interrelated practices shaped the implementation of the new production system. We also identify core components and dynamics that constitute a richer multi-dimensional view of the IS strategy implementation (alignment) process. In particular, we identify three salient factors that contribute to strategy blindness – mistranslation of intent, flexibility of the IT artifact and cognitive entrenchment – and discuss how they affect strategic implementation processes. We conclude by discussing implications of our findings for IS strategy theory and practice, especially the contribution of strategy-as-practice to this stream of research.     

企业云应用演进策略多时段分析

随着云计算技术的发展,企业急需一种有效方法将原本孤立的应用系统向云平台迁移。将网络层次分析法(ANP)及其超级矩阵收敛过程应用于企业云应用演进计划制定,提出一个演进策略的多时段分析方法。通过对企业云应用体系结构的建模与仿真分析,构建ANP多属性决策模型,解析超级矩阵从初始状态到极限状态的收敛过程,挖掘各云应用系统的分时段关键性影响因素,为企业的整体演进策略提供支持。最后,通过一个案例展示多时段分析方法的具体过程,提取出相关关键因素,为企业策略的动态规划提供理论依据。     

基于无传感器的PMSM电流控制策略的研究

提出一种新型的滑模观测器,并分别研究在4种不同的电流控制策略下,基于该新型滑模观测器的PMSM伺服系统的控制问题。该新型滑模观测器引进了Sigmoid函数作为控制函数用来抑制抖振,并根据PMSM的反电动势模型构建了反电势观测器来提取所需的连续信号,因此取消了传统的一阶低通滤波器和相角补偿环节。为了对电机的转子位置和转速进行更加精确的估算,引入了转子位置锁相环结构。在Matlab/Simulink平台基础上建立了4种不同的电流控制策略,基于新型滑模观测器PMSM无位置传感器三闭环控制系统仿真模型,分别对反电动势估算、速度估算、位置估算和突加负载扰动进行了仿真分析。仿真结果表明,该新型滑模观测器在4种不同的电流控制策略下,对电机转子位置和转速的估算、电磁转矩以及定子三相电流有着不同的影响,验证了该新型滑模观测器算法的可行性。     

游戏产品有效粘合用户时间的策略研究

通过对游戏的分类、发展历程梳理以及用户的需求分析,结合游戏产生过程给出了游戏产品有效粘合用户时间的策略,最后预测了游戏的发展趋势。