数控机床操控器人机界面优化设计研究

目的控制器和显示器共同组成数控机床控制面板的整体界面,是机床接受与执行命令的交互平台。从人机交互角度,聚焦于控制器的界面布局进行优化设计。方法基于人机工程学理论的优化流程,采用现场访谈、现场观察等方法,将人机工程学的理论转化为具体考核指标。结论从人机工程学的研究角度出发,结合工业设计、用户体验设计学等内容,从功能区域分区、操纵器色彩设计等方面优化数控机床控制器的界面,提高系统整体效能及使用者满意度,为数控机床系统开发设计提供参考。     

Noise analysis of robot manipulator using neural networks

Due to a lot of robot manipulators application in industry, low noise degree is very important criteria for robot manipulator's joints. In this paper, joint noise problem of a robot manipulator with five joints is investigated both theoretically and experimentally. The investigation is consisted of two steps. First step is to analyze the noise of joints using a hardware and software. The hardware is a part of noise sensors. The second step; according to experimental results, some neural networks are employed for finding robust neural noise analyzer. Five types of neural networks are used to compare each other. From the results, it is noted that the proposed RBFNN gives the best results for analyzing joint noise of the robot manipulator.     

低成本单伺服注塑机械手控制系统设计

在注塑行业,注塑机械手已经逐渐替代人工操作并发挥着重要作用,而注塑机械手的精度又直接影响到注塑机的工艺和注塑件的质量.针对目前注塑机械手存在部分问题的现状,设计了一种基于STM32单片机的高精度低成本的注塑机械手控制系统,并对其硬件系统和软件系统做了详细的介绍.经过实验测试,注塑机械手达到了预期的功能和控制精度,但是其价格相比工业上的注塑机机械手降低了30％.     

Intelligent adaptive observer-based optimal control of overhead transmission line de-icing robot manipulator

In cold season, wet snow ice accretion on overhead transmission lines increases wind load effects which in turn increases line tension. This increased line tension causes undesirable effects in power systems. This paper discusses the design of an observer-based boundary sliding mode control (BSMC) for 3 DOF overhead transmission line de-icing robot manipulator (OTDIRM). A robust radial basis functional neural network (RBFNN) observer-based neural network (NN) controller is developed for the motion control of OTDIRM, which is a combination of BSMC, NN approximation and adaptation law. The RBFNN-based adaptive observer is designed to estimate the positions and velocities. The weights of both NN observer and NN approximator are tuned off-line using particle swarm optimization. Using Lyapunov analysis the closed loop tracking error was verified for a 3 DOF OTDIRM. Finally, the robustness of the proposed neural network-based adaptive observer boundary sliding mode control (NNAOBSMC) was verified against the input disturbances and uncertainties.     

Dynamic neural network method-based improved PSO and BR algorithms for transient probabilistic analysis of flexible mechanism

To improve the computing efficiency and precision of transient probabilistic analysis of flexible mechanism, dynamic neural network method (DNNM)-based improved particle swarm optimization (PSO)/Bayesian regularization (BR) (called as PSO/BR-DNNM) is proposed based on the developed DNNM with the integration of extremum response surface method (ERSM) and artificial neural network (ANN). The mathematical model of DNNM is established based on ANN on the foundation of investigating ERSM. Aiming at the high nonlinearity and strong coupling characteristics of limit state function of flexible mechanism, accurate weights and thresholds of PSO/BR-DNNM function are discussed by searching initial weights and thresholds based on the improved PSO and training final weights and thresholds by the BR-based training performance function. The probabilistic analysis of two-link flexible robot manipulator (TFRM) was investigated with the proposed method. Reliability degree, distribution characteristics and major factors (section sizes of link-2) of TFRM are obtained, which provides a useful reference for a more effective TFRM design. Through the comparison of three methods (Monte Carlo method, DNNM, PSO/BR-DNNM), it is demonstrated that PSO/BR-DNNM reshapes the probability of flexible mechanism probabilistic analysis and improves the computing efficiency while keeping acceptable computational precision. Moreover, the proposed method offers a useful insight for reliability-based design optimization of flexible mechanism and thereby also enriches the theory and method of mechanical reliability design.     

Boundary Control of a Flexible Robotic Manipulator With Output Constraints

In this study, we consider a boundary control problem of a flexible manipulator with input disturbances and output constraints, achieving pre‐set performance attributes on position tracking error and the deflection error at the end of the beam. The dynamics of the system are represented by partial differential equations (PDEs). With the Lyapunov's direct method, a boundary controller with disturbance observer is designed to regulate the angular position and suppress elastic vibration simultaneously. The proposed control scheme allows the errors to converge to an arbitrarily small residual set, with convergence rate larger than a pre‐specified value. Numerical simulations demonstrate the effectiveness of the proposed scheme.     

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.     

基于Kinect的机械臂增强现实示教研究

机械臂广泛地应用在工业自动化生产以及人们日常生活中,机械臂而示教学习作为一种重要的运动规划方式,是机械臂研究领域的一项重要研究内容。鉴于此,设计了一种基于Kinect的虚拟机械臂增强现实示教系统,通过Kinect传感器采集人手位置数据,利用机械臂逆运动学模型驱动虚拟机械臂跟踪人手运动,实现对机械臂的虚拟示教;利用增强现实技术,将虚拟机械臂叠加到真实环境中,实现对机械臂的增强现实示教。实验结果表明该系统能够将虚拟机械臂准确地叠加到真实环境中,并实时跟踪人手运动,系统具有良好的交互性。     

矩形顶管施工对下卧轨道交通盾构隧道 变形影响的数值模拟

针对苏州市综合管廊项目,为确保邻近既有轨道交通结构的安全,通过midas GTS模拟综合管廊与轨道交通交叉段的矩形顶管施工过程,研究综合管廊顶管施工对下卧轨道交通盾构隧道结构变形的影响。模拟结果认为施工引起的隧道变形在允许的范围之内,不会影响轨道交通正常运营。研究结果可对后续上穿轨道交通类似工程提供参考。     

智能温度传感芯片中Δ-Σ调制器的设计

从模数转换的基本理论出发,在对一阶Δ-Σ调制器原理深入解析的基础上,得到Δ-ΣADC动态输入范围的计算方法。利用Matlab simulink建立了二阶Δ-Σ调制器系统模型,对调制器电路进行仿真和参数优化,对其性能进行了有效评估。使用轨对轨折叠式共源共栅运算放大器作为调制器的积分器,增大了调制器的动态输入范围;设计的高速比较器将NMOS负载管交叉耦合从放大器输出端引入正反馈,提高了转换速度。设计实现了一款适用于14 bit温度转换芯片的二阶△-∑调制器,信噪比SNR可达87 dB。