时滞分布参数系统的移动传感器/执行器防碰撞控制

针对一类状态时滞的分布参数系统,考虑了传感器/执行器间的防碰撞问题和最大通讯距离的最小通讯能耗问题,以及系统的稳定性问题.利用抽象发展方程理论和Lyapunov稳定性方法,设计了一种基于时滞分布参数系统的智能体移动控制策略,包括输出反馈控制器和移动控制力.通过理论推导和仿真实验验证,文中设计的控制策略能够使得时滞分布参数系统是渐近稳定的,同时智能体在移动过程中是防碰撞的,也验证了智能体在最大通讯距离的最小能耗.     

基于移动传感器/执行器网络的时滞分布参数系统镇定控制

考虑一类基于移动传感器/执行器网络具有状态时滞的分布参数系统,在系统中加入扰动因子,分析移动传感器/执行器的动力学行为,研究系统出现扰动时如何设计反馈控制器和移动控制力.首先利用无穷维抽象发展方程理论将时滞分布参数系统在Hilbert空间中进行方程演变;其次,结合工程实际应用进行合理的假设以便于问题的解决;接着利用算子...     

基于观测器的移动执行器对二维分布参数系统的控制

研究二维分布参数系统在传感器执行器网络下的控制问题.传感器执行器网络由二维平面上固定的传感器与移动的执行器组成.首先,利用传感器对二维分布参数系统的测量信息设计观测器,用来估计二维分布参数系统的状态,并在观测器的基础上给出相应的控制器;然后,利用算子半群理论并结合Lyapunov方法,得到平面上移动的执行器的水平运动速度和垂直运动速度,该速度依赖于观测器的信息;最后,数值仿真表明,二维分布参数系统在该移动执行器控制下的性能得到了有效的提高.     

一类活动边界分布参数系统的移动控制策略

针对一类具有活动边界的分布参数系统,考虑移动传感器/执行器的动力学行为,研究其移动控制问题.考虑并列的传感器/执行器,通过传感器对系统的状态进行测量并将测量值传递给执行装置中的控制器.根据传感器之间不同的信息传递方式分别设计相应的控制器,基于无穷维抽象发展方程理论和Lyapunov方法得到相应的移动控制策略,并证明所提出的移动控制策略与系统的活动边界之间的关系.最后通过仿真结果验证所提出策略的有效性.     

UHF频段RFID系统防碰撞算法研究

防碰撞技术是决定RFID系统性能的关键因素之一,特别是UHF频段.防碰撞性能决定着多目标的识别率、识别速度.本文着重研究UHF频段RFID系统防碰撞解决方案和算法改进问题,探讨盘存周期内总时隙数的选取,并对系统效率进行仿真,提出简单易行的提高系统效率的方法.     

基于多传感信息融合的车辆主动防碰撞控制系统

多传感信息融合或称多源信息融合是近年来发展起来的一门新技术。针对车辆防碰撞系统工作环境恶劣、干扰因素众多、单一传感器判断易产生虚警的特点，本文阐述了多传感信息融合技术在车辆防碰撞系统中的应用，并给出了系统的组成、功能。传感器的选择以及融合策略。     

自动导引车系统防碰撞及死锁的形式化控制方法

针对自动导引车系统中的协调控制问题,提出一种基于有向图的控制程序自动化设计方法.首先,根据自动导引车系统的结构建立基于区域控制的有向图模型;其次,在部分可观的条件下,定义扩充危险域的概念,给出一种估计危险域中车辆数目的方法,进而给出导引路径的防碰撞控制规范;最后,讨论系统发生死锁的两个条件,给出相应的死锁控制方法,并通过仿真实验验证了所提方法的有效性.     

二阶分布参数系统的变结构控制

本文研究了Hilbert空间中的二阶分布参数系统的变结构控制问题,给出了系统存在滑动模的条件;并研究了系统的有限维近似问题,从而为柔性机器人等分布参数系统的变结构控制奠定了理论基础。     

基于Hash函数的RFID系统防碰撞算法的研究

防碰撞算法是RFID系统的关键技术之一;针对动态帧时隙ALOHA算法(EDFSA)的局限性,提出了一种基于Hash函数的防碰撞算法;在算法中,标签通过Hash函数选择时隙发送信息,阅读器通过精确的标签数目估计方法来动态改变帧长度,从而提高了系统识别效率;文中详细介绍了算法设计流程,通过建立数学模型对算法进行分析,证明了系统识别效率期望值突破了36.8%的限制,仿真实验进一步证明了该算法在识别大量标签时效率明显优于动态帧时隙ALOHA算法.     

RFID系统防碰撞协议的研究

碰撞问题是影响RFID系统读取效率的关键问题。分析了RFID系统中二进制树和查询树的防碰撞原理,并针对这些协议在对碰撞连续的标签进行识别时操作效率较低的问题,提出了一种新的协议。该协议是在二者的基础上进行改进的,对三种防碰撞协议的性能进行了比较,新协议能更好地解决射频识别系统中多个标签识别的问题。     

Formation control for multi-robot systems with collision avoidance

In this paper, distributed formation is studied for a team of mobile robots including leaders and followers. Followers are able to sense the relative displacements to neighbouring followers and all of the leaders, and the leaders can be sensed by the followers. Based on such assumption of sensing, distributed formation control scheme is designed, under which both followers team and leaders team are fully independent. The followers and leaders have exchangeable roles within their own group. The leaders can have an arbitrary formation, and around the leaders, the followers need to reach a regular polygon formation with a suitable orientation. Distributed control laws and localised collision avoidance algorithms are designed for each follower, and they use only local displacements. Speed and acceleration sensors are avoided. As the leaders and the followers are independent and exchangeable, both robot teams are scalable and robust against member failures and system delays.     

On-line collision avoidance system for two PTP command-based manipulators with distributed controller

This research aims to solve online collision avoidance problem of two manipulators with independent controller. Since industrial robot controller is a closed commercial system, trajectory generation part of robot controlling is always proprietary or unknown. Thus, this paper proposes a collision avoidance system of two manipulators which are controlled by point-to-point (PTP) commands, in condition that the internal of robot controller is unknown and unchangeable. Based on this condition, collision avoidance is supposed to be realized by online scheduling of these PTP controlling commands. This paper proposes the collision avoidance method that assumes the three-dimensional common workspace between two manipulators can be partitioned into many subregion elements. And with managing these subregion elements, which are occupied by robot motion, PTP commands are scheduled to adjust execution timing for collision avoidance. A deadlock problem caused by the partition of the workspace is also taken into consideration in the method. And the effectiveness and efficiency of the method have been verified by simulations and experiments.     

DNN-state identification of 2D distributed parameter systems

There are many examples in science and engineering which are reduced to a set of partial differential equations (PDEs) through a process of mathematical modelling. Nevertheless there exist many sources of uncertainties around the aforementioned mathematical representation. Moreover, to find exact solutions of those PDEs is not a trivial task especially if the PDE is described in two or more dimensions. It is well known that neural networks can approximate a large set of continuous functions defined on a compact set to an arbitrary accuracy. In this article, a strategy based on the differential neural network (DNN) for the non-parametric identification of a mathematical model described by a class of two-dimensional (2D) PDEs is proposed. The adaptive laws for weights ensure the ‘practical stability’ of the DNN-trajectories to the parabolic 2D-PDE states. To verify the qualitative behaviour of the suggested methodology, here a non-parametric modelling problem for a distributed parameter plant is analysed.     

基于预测窗的轮式移动机器人最优避障避碰算法

针对非线性轮式移动机器人的避障以及多机器人间的相互避碰问题,提出了一种基于预测窗的避障避碰算法.首先为了便于预测碰撞的发生,通过反馈线性化将非线性的机器人运动学模型转化成线性模型;然后根据线性模型预测会导致机器人发生碰撞的所有相对虚拟加速度变化量集合,称之为加速度变化障碍.基于此,为每个机器人构造既能躲避障碍物又能相互避碰的可行加速度变化集合.然后通过优化指标函数求得最优虚拟加速度变化量,最后将其转换成机器人的实际控制量.这种算法与现有的相比,可使机器人在避障或避碰过程中的行驶方向角、线速度的变化幅值更小,角速度和线加速度的变化更为平顺,而且运行所用的平均时间更短.仿真结果演示了所提出算法的有效性和相对于已有方法的优势.     

基于局部信息的移动感知网覆盖方法

移动感知网是一个由许多带有传感器的自主移动机器人组成的分布式传感器网络。为了更好地部署这些移动机器人节点,形成最大化覆盖感知区域,提出了一种基于机器人局部信息的分布式感知网覆盖方法。每个节点利用与邻居节点之间的虚拟人工势场产生的虚拟作用力来控制移动节点的运动和节点间的避碰,使移动节点能够在允许的时间内,以较少的能量消耗移动到各自理想的位置。采用李亚普诺夫函数进行了感知网节点势场梯度的理论分析,用计算机仿真实验验证了该方法的有效性,并与模拟退火算法进行了性能比较。     

基于改进速度障碍法的多机器人避碰规划算法

针对多移动机器人运动协调中的动态安全避碰问题,在分析速度障碍法原理的基础上,设计用于机器人之间相互避让的互动速度法则,并通过制定机器人的碰撞时间、碰撞距离因子对构型障碍的大小进行实时调整,把运动障碍物、动力学约束下的多步可达窗口、目标点都映射到一种速度变化空间当中,使多机器人的动态避碰问题转化为一种最优化问题,并构造了新的优化评价函数;设计了基于改进速度障碍法的机器人动态避碰规划算法。仿真实验表明,该方法有效地克服了碰撞冲突,实现了多机器人之间的运动协调控制,提高了机器人追踪运动目标的快速性。     

Modal consensus observers for distributed parameter systems

This article proposes a new type of a consensus protocol for the synchronization of distributed observers in systems governed by parabolic partial differential equations. Addressing the goal of sharing useful information among distributed observers, it delves into the details governing the modal decompositions of distributed parameter systems. Assuming that two different groups of sensors are available to provide process information to the two distributed observers, the proposed modal consensus design ensures that only useful information is transmitted to the requisite modal components of each of the observers. Without any consensus protocol, the observers capture different frequency content of the spatial process in differing degrees, as it relates to the concept of modal observability. Their modal components exhibit different learning behavior toward the process state. In the extreme case, it turns out that certain modal components of the distributed observers occasionally behave as naïve observers. To ensure that, both collectively and modal componentwise, the observers agree both with the process state and with each other, a modal component consensus protocol is proposed. Such a consensus protocol is mono-directional and provides only useful information necessary to the appropriate modal component of the distributed filters that behaves as a naïve modal observer. This protocol, when abstracted and applied to different state decompositions can be viewed as mono-directional projections of information transmitted and received by the participating distributed observers. Detailed numerical studies of advection PDE in one and two spatial dimensions are included to elucidate the details of the proposed modal consensus observers.     

A bounded distributed connectivity preserving aggregation strategy with collision avoidance property

This paper presents a bounded connectivity preserving control strategy for the aggregation of multi-agent systems. The problem is investigated for two cases of single-integrator agents and unicycles. Under the proposed control strategy, if two agents are in the connectivity range at some point in time, they will stay connected thereafter. The agents finally aggregate while avoiding collision in such a way that the average of the distances between every pair of neighboring agents is bounded by a pre-specified positive real number, which can be chosen arbitrarily small. The results are developed based on some important characteristics of the positive limit set of the closed-loop system under the proposed control strategy and a fundamental property of convex real functions. The theoretical results are verified by simulation.