增强型蓝牙基带系统的设计与实现

论文采用SOPC方案完成了增强型蓝牙基带系统的设计和实现。经测试,该系统能正常通信。同时,该系统与蓝牙基带系统相比,其安全性和抗干扰性能均得到提高,使得该基带系统能应用于银行、军事等领域。     

专科学校学生选课网络管理信息系统的分析与实现

本文介绍了学生选课网络管理信息系统。文章从实际出发,叙述了该系统的应用前景,详细分析了该系统的功能和特点,特别强调了系统实体之间关系和人机界面问题,并给出了该系统的网络软件、硬件的实现框图。在文末还提出了提高系统速度方面的措施。实践证明:该系统运行可靠,实用性强,是一个成功的网络管理信息系统应用实例。     

基于网络通讯的机器人足球比赛仿真系统

提出了一种基于网络通讯的客户-服务器模式的机器人足球比赛系统。该系统充分模拟了实际的机器人足球比赛过程。该仿真系统应用在1999年首届全国机器人足球比赛中。通过比赛,该仿真系统在系统稳定性,客户端开发平台无关性和系统操作的灵活性方面都得到了很好的证明。而且,该仿真系统可以作为一个通用的多Agent系统协作和分布式人工智能研究平台,且对于进一步开发机器人遥操作技术也提供了一些有益的尝试。     

基于LabVIEW的co多点采集远程监测系统的研究

介绍了LabVIEW基本知识,提出了一氧化碳多点采集远程监测系统。重点阐述了该系统的硬件构建和软件设计,该系统运行稳定,性能可靠,能满足一般科研需要。该系统可扩展性和实用性很强,稍加改造即可用于居民用户或者工厂。     

一个新超混沌系统的动力学分析及其电路实现

构造了一个新的超混沌系统,通过Matlab绘制其相轨迹图,初步判断该系统具有混沌吸引子。从平衡点、对称性和不变性、耗散性和混沌吸引子的存在性、Lyapunov指数谱以及Poincare截面,对该新超混沌系统从定性和定量方面进行了详细的动力学分析,加深了对该超混沌系统的认识。最后,搭建了Multisim电路对该超混沌系统进行电路仿真实验,实验结果与Matlab数值模拟结果相一致,验证了该系统的实际超混沌特性。     

基于虚拟仪器零件检测的应用研究

介绍了机器视觉的基本原理与虚拟仪器的设计思想,指出二者各自以及结合的优势。由此,构建一种基于虚拟仪器的机器视觉零件检测系统。该文中以检测方块和圆环为例验证该系统的功能。该系统利用机器视觉实现检测的自动化,同时提高系统的可扩展性。实验表明:该系统的检测的速度和精度可以满足工作地需求,而且操作简单,系统是有效的,可行的。     

基于共享物理存储空间的松耦合存储管理机制

引入一种NUMA多处理器原型系统,分析该系统上的操作系统对物理内存管理的特点。基于该系统设计和实现了一个全局共享内存系统,使操作系统充分利用整个系统上的物理内存,减少应用程序的执行时间。实验结果表明,该系统能够更好地支持存储密集型 应用。     

一类新型Chua's电路的Lagrange稳定性分析

构造一类新型Chua’s电路,研究该系统的Lagrange稳定性。对于给定参数,首先计算得到该系统具有正的Lyapunov指数,说明该系统具有混沌特性,然后证明该系统具有全局指数吸引集和正向不变集。对于该系统的三个不稳定平衡点,设计线性控制器,实现平衡点的全局指数稳定控制。数值仿真验证了结论的正确性。     

矿井灾害预警救援与环境预测一体化系统设计

针对灾害预警救援系统和环境预测系统由于是独立运行而具有局限性的问题,提出了一种矿井灾害预警与环境预测一体化系统的设计方案;给出了该系统设计思路及架构,阐述了该系统中相互关联的数据采集、灾害预警、救援指挥和环境预测4个子系统的设计原理,介绍了该系统人机界面的结构及设计原则。该系统的研究对井下救援工作具有重要意义。     

一种新的轻量级认证系统模型

本文提出了一种新的认证系统模型,该模型改变了传统认证系统的架构,利用分布式哈希表结构,实现了一种轻量级的认证系统。通过对本系统的分析表明,该系统与现有的认证系统相比,该系统具有同等的认证安全性和良好的可靠性、扩展性以及系统性能。     

基于非结构模型机器人力控制稳定性分析*

本文将机械手和接触环境作为一个整体来考虑，采用非结构模型分析了机器人力外环控制的稳定性。得到了机器人力控制系统稳定操作的界限，实验结果表明这种分析方法的合理性。     

基于不确定逼近的机械手自适应鲁棒预测控制

针对具有参数不确定性和未知外部干扰的机械手轨迹跟踪问题提出了一种多输入多输出自适应鲁棒预测控制方法. 首先根据机械手模型设计非线性鲁棒预测控制律, 并在控制律中引入监督控制项; 然后利用函数逼近的方法逼近控制律中因模型不确定性以及外部干扰引起的未知项. 理论证明了所设计的控制律能够使机械手无静差跟踪期望的关节角轨迹. 仿真验证了本文设计方法的有效性.     

基于xPC Target的机械臂控制系统开发

介绍了控制系统的快速控制原型化设计方法以及xPC目标环境,然后基于xPC目标环境和Mathworks公司的Matlab RTW(real-time workshop,实时工作间),Simulink,Stateflow等工具开发了一个机械臂的控制系统。实验结果表明,该软件系统能够很好地控制机械臂抓取目标物体。     

考虑驱动系统动态的机械手神经网络控制及应用

针对结构和参数均未知的机械手控制问题, 提出了考虑驱动系统动态的机械手神经网络控制方法, 采用稳定的径向基(Radial basis function, RBF)神经网络辨识机械手未知动态, 而附加的鲁棒控制可以保证存在神经网络的建模误差和外部干扰时系统的稳定性和性能, 并且该方法使机械手闭环系统一致最终有界. 同时开发了基于半实物仿真技术的机械手控制系统, 最后, 将本文方法与经典的PD控制器和自适应控制器在同一机械手平台上进行了实验验证与分析, 实验结果表明该方法具有良好的控制性能.     

Towards nonadaptive and adaptive control of manipulation robots

Control synthesis for robotic systems with a variable payload is considered. First, we synthesize a robust, nonadaptive decentralized control using an approximative system model. Then, we analyze the stability of an exact system model. We thus check whether the robotic manipulator is stabilized for all allowable payload variations. If the simple decentralized control cannot accommodate all expected payload variations we introduce additional load, nonadaptive, feedback loop. This global control requires force transducers to be implemented in manipulator joints. If such nonadaptive control cannot stabilize robotic manipulator trajectories we suggest another adaptive control scheme. This control scheme includes an algorithm for on-line identification of variable payload and adaptation of local gains.     

基于RBF-BP算法的机械臂多自由度分拣控制系统设计

为提升机械臂设备的准确分拣能力,设计基于RBF-BP算法的机械臂多自由度分拣控制系统。利用RBF-BP前馈神经网络,规划机械臂设备的运动轨迹路线,实现基于RBF-BP算法的机械臂运动轨迹建模。确定工业相机在总功能框架中所处连接位置,根据机械臂选型情况,确定可编程逻辑控制器、变频控制器对于所选机械臂元件的调节能力,完成对系统功能模块的开发。借助传输信道,将Sorting分拣指令、ToolControl控制指令反馈回核心控制主机,建立完整的指令执行回路,再联合相关硬件设备结构,实现基于RBF-BP算法的机械臂多自由度分拣控制系统设计。实验结果表明,在抓取能力相同的情况下,应用RBF-BP算法控制系统机械臂成功分拣的工件数量为19件,机械臂抓取成功率为95%,说明所设计系统满足提升机械臂准确分拣能力的设计初衷。     

Analysis and Verification of Repetitive Motion Planning and Feedback Control for Omnidirectional Mobile Manipulator Robotic Systems

Mobile manipulator robotic systems (MMRSs) composed of a manipulator and a mobile platform are investigated in this paper. In order for the mobile manipulator robotic system (MMRS) to return to its initial state when the manipulator’s end-effector is requested to execute cyclical tasks, a quadratic program (QP) based repetitive motion planning and feedback control (RMPFC) scheme is proposed and analyzed. Such an RMPFC scheme can not only mix motion planning and reactive control, but also consider the physical limits of the robotic system. Mathematically, the efficacy of the RMPFC scheme is verified via gradient dynamics analysis. To further demonstrate the effectiveness of the RMPFC scheme, a kinematically redundant MMRS composed of a three degrees-of-freedom (DOF) planar manipulator and an omnidirectional mobile platform is designed, modeled and analyzed. Then, repetitive motion planning and feedback control for the designed omnidirectional MMRS is studied. Besides, a numerical algorithm is developed and presented to solve the QP and resolve the redundancy of the robotic system. Moreover, computer simulations are comparatively performed on such an omnidirectional MMRS, and simulation results substantiate the effectiveness, accuracy and superiority of the proposed RMPFC scheme.     

Robust tracking control for rigid robotic manipulators

The problem of robust tracking control using a nominal feedback controller and a variable structure compensator for a rigid robotic manipulator with uncertain dynamics is addressed in this note. It is shown that the effects of large system uncertainties can be eliminated and asymptotic convergence of the output tracking error can be guaranteed by using a variable structure compensator in the closed loop feedback control system for the rigid robotic manipulator     

End‐Point Regulation and Vibration Suppression of a Flexible Robotic Manipulator

In this paper, end‐point regulation and vibration suppression are investigated for a flexible robotic manipulator subject to the external disturbances. The dynamics of the flexible robotic manipulator is represented by one partial differential equation (PDE) and five ordinary differential equations (ODEs). Based on the Lyapunov's direct method, boundary control is developed to drive the manipulator to the desired set‐point and simultaneously suppress the vibrations of the flexible manipulator. Considering the unknown spatiotemporally varying disturbance, uniform boundedness of the closed‐loop system is achieved. The control performance of the closed‐loop system is guaranteed by suitably choosing the design parameters. Simulations are provided to illustrate the effectiveness of the proposed control.     

Sliding mode-based adaptive tube model predictive control for robotic manipulators with model uncertainty and state constraints

In this paper, the optimal tracking control for robotic manipulatorswith state constraints and uncertain dynamics is investigated, and a sliding mode-based adaptive tube model predictive control method is proposed. First, utilizing the high-order fully actuated system approach, the nominal model of the robotic manipulator is constructed as the predictive model. Based on the nominal model, a nominal model predictive controller with the sliding mode is designed, which relaxes the terminal constraints, and realizes the accurate and stable tracking of the desired trajectory by the nominal system. Then, an auxiliary controller based on the node-adaptive neural networks is constructed to dynamically compensate nonlinear uncertain dynamics of the robotic manipulator. Furthermore, the estimation deviation between the nominal and actual states is limited to the tube invariant sets. At the same time, the recursive feasibility of nominal model predictive control is verified, and the ultimately uniformly boundedness of all variables is proved according to the Lyapunov theorem. Finally, experiments show that the robotic manipulator can achieve fast and efficient trajectory tracking under the action of the proposed method.