Improved Disturbance Observer (DOB) Based Advanced Feedback Control for Optimal Operation of a Mineral Grinding Process

Advanced feedback control for optimal operation of mineral grinding process is usually based on the model predictive control (MPC) dynamic optimization. Since the MPC does not handle disturbances directly by controller design, it cannot achieve satisfactory effects in controlling complex grinding processes in the presence of strong disturbances and large uncertainties. In this paper, an improved disturbance observer (DOB) based MPC advanced feedback control is proposed to control the multivariable grinding operation. The improved DOB is based on the optimal achievable H 2 performance and can deal with disturbance observation for the nonminimum-phase delay systems. In this DOB-MPC advanced feedback control, the higher-level optimizer computes the optimal operation points by maximize the profit function and passes them to the MPC level. The MPC acts as a presetting controller and is employed to generate proper pre-setpoint for the lower-level basic feedback control system. The DOB acts as a compensator and improves the operation performance by dynamically compensating the setpoints for the basic control system according to the observed various disturbances and plant uncertainties. Several simulations are performed to demonstrate the proposed control method for grinding process operation.

Application and Analysis of Force Control Strategies to Deburring and Grinding

This paper aims to give an insight into the development and evaluation of force controlled machining processes with a commercially available setup. We will focus on a deburring and a grinding scenario, representing the major applications in today’s robot machining. Whereas the deburring use-case implements a force dependent feed-rate control, the grinding use-case implements an orthogonal force (pressure) control. Both strategies will be evaluated and the influence of general machining and robot specific parameters will be discussed.

Multiparameter Optimization and Controlling for Cylindrical Grinding Process

This paper bursts the bondage of conventional no-burn thought, presents an optimum strategy permitting burn appear in grinding roughing stage, but the burning layer can be summed on the following finishing stage. On the base of the basic grinding models, the objective function and constrained functions for the multiparameter optimum grinding models had been built in this paper. By the computer simulation, the nonlinear optimum grinding control parameters had been obtained, and the truth grinding process had been controlled by these parameters. The results of simulation and the experiments proved the exactitude of the optimum models and the feasibility of the optimum strategy. This paper had also created the precondition for the grinding automation, virtual grinding and intelligent grinding system for cylindrical grinding process.

Dynamics and Control of Grinding Machine with Micropositioning Workpiece Table

To improve the machining precision of a surface grinding machine, a micropositioning workpiece table with high performance was used as auxiliary infeed mechanism to implement nanometer level positioning and dynamic compensation. To better understand the characteristics of the grinding machine modulated with micropositioning workpiece table, the dynamic model of the grinding system was established with modal synthesis and Lagrange＇s equation methods. The grinding system was divided into five subsystems. For each subsystem, the generalized kinematic and potential energies were obtained. Accordingly the dynamic model of the grinding system was given in the modal domain. The waviness of the grinding process was achieved based on the wheel and workpiece vibration. A nonlinear proportional integral derivative （PID） controller with differential trackers was developed to realize dynamic control. The simulation results show that the machining accuracy of the workpiece can be effectively improved by utilizing the micropositioning workpiece table to implement dynamic compensation. An experimental test was carried out to verify the proposed method, and the waviness of the workpiece can be reduced from 0.46 μm to 0.10 μm.

Impact of Different Grinding Aids on Standard Deviation in X-Ray Fluorescence Analysis of Cement Raw Meal

X-ray fluorescence (XRF) analysis utilizes particle size which is resulted from milling of a material. The milling ensures uniform and fine grained powder. The finer and more uniform the particle size is, the better the result and easier it is for material quality control. To ensure uniformity in particle size and finer powder, a comparative analysis was conducted with different grinding aids and pressed pellet method was used in obtaining analysis results. Pressed pellets of cement raw meal sample milled with different grinding aids (graphite, aspirin and lithium borate) were subjected to XRF. Graphite produced better particle size uniformity with a corresponding standard deviation that made quality control of raw meal easier and better than aspirin and lithium borate.

Corner Transition Toolpath Generation Based on Velocity-Blending Algorithm for Glass Edge Grinding

Sharp corners usually are used on glass contours to meet the highly increasing demand for personalized products,but they result in a broken wheel center toolpath in edge grinding.To ensure that the whole wheel center toolpath is of G1 continuity and that the grinding depth is controllable at the corners,a transition toolpath generation method based on a velocity-blending algorithm is proposed.Taking the grinding depth into consideration,the sharp-corner grinding process is planned,and a velocity-blending algorithm is introduced.With the constraints,such as traverse displacement and grinding depth,the sharp-corner transition toolpath is generated with a three-phase motion arrangement and with confirmations of the acceleration/deceleration positions.A piece of glass with three sharp corners is ground on a three-axis numerical-control glass grinding equipment.The experimental results demonstrate that the proposed algorithm can protect the sharp corners from breakage efficiently and achieve satisfactory shape accuracy.This research proposed a toolpath generation method based on a velocity-blending algorithm for the manufacturing of personalized glass products,which generates the transition toolpath as needed around a sharp corner in real time.

Proportion Integration Differentiation(PID)Control Strategy of Belt Sander Based on Fuzzy Algorithm

Aiming at solving the problems of response lag and lack of precision and stability in constant grinding force control of industrial robot belts,a constant force control strategy combining fuzzy control and proportion integration differentiation(PID)was proposed by analyzing the signal transmission process and the dynamic characteristics of the grinding mechanism.The simulation results showed that compared with the classical PID control strategy,the system adjustment time was shortened by 98.7%,the overshoot was reduced by 5.1%,and the control error was 0.2%-0.5%when the system was stabilized.The optimized fuzzy control system had fast adjustment speeds,precise force control and stability.The experimental analysis of the surface morphology of the machined blade was carried out by the industrial robot abrasive grinding mechanism,and the correctness of the theoretical analysis and the effectiveness of the control strategy were verified.

复杂曲面机器人磨抛技术研究现状与趋势展望综述

在航空、能源、交通、军工等国家战略领域中,针对复杂曲面零件的自动化、高质量和高效率磨抛需求,对近年来国内外工业机器人磨抛加工关键技术及集成系统的研究和应用进展进行了综述。首先,从复杂曲面机器人磨抛机理及工艺优化、磨抛运动轨迹规划、磨削力控制等方面总结了复杂曲面机器人磨抛技术的研究成果;然后,介绍了国内外机器人磨抛集成系统应用现状;最后,分析了复杂曲面机器人磨抛技术的主要问题以及发展趋势,为该技术的发展提供了重要的指导和方向。研究结果表明:当前该技术存在的主要问题包括磨抛机理不够清晰,数学模型不够准确,复杂曲面机器人磨抛轨迹规划效率不高,磨抛力的控制仍不够精准等;另外,磨抛工艺参数优化、机器人力位混合控制、机器人高精度标定与误差补偿、基于数字孪生的机器人磨抛在线监控、机器人磨抛细分应用场景等方面的研究和实践将极大地推动机器人磨抛技术的发展和应用。

钢轨打磨车专用EHA非线性反演控制

为提高钢轨打磨车打磨钢轨的平顺性及稳定性,提出以电动静液作动器(EHA)代替传统液压作动系统作为钢轨打磨车的专用执行器,考虑柱塞泵的总效率波动和液压缸动静摩擦差异大2个非线性因素,建立非线性数学模型;建立EHA的MATLAB、AMESim联合仿真模型,对PID控制、滑模变结构控制、反演控制进行控制策略对比研究,仿真分析验证反演控制在响应快速性及稳定性方面具有良好的表现。搭建四象限平台对EHA进行反演控制负载试验,结果表明:其位移控制精度达0.21 mm,具有较好的控制性能。

基于神经网络参数自学习的阻抗控制

针对机器人在打磨过程中环境刚度和位置未知,传统的阻抗控制难以有效保持打磨质量的问题,提出了一种基于调节参数神经网络自学习的阻抗控制。由于基于李雅普诺夫稳定性理论设计的阻尼参数补偿方法中调节参数的选取直接影响系统的控制性能,根据阻尼补偿的数学描述,构建神经网络,用于其参数自适应调节,设计不同的激励函数用于反映阻尼在多种因素影响下变化的特征。通过所搭建的神经网络在线学习,实现参数的优化,以适应打磨过程环境变化。在斜面、平面及曲面等不同环境下,考虑其刚度突变、刚度动态变化、期望力动态变化等因素的仿真实验,结果表明所提出的控制方法与传统控制方法相比,具有更小的超调和稳态误差,并能够适应环境参数未知的情况,明显提高打磨质量和效率。

高精度工具磨床摆轴模糊自整定控制方法研究

针对精加工刀具刃磨过程所需工具磨床摆轴回转运动的高精度要求,设计了新型的高精度工具磨床摆轴及其控制系统。首先,根据已设计的摆轴机械结构建立系统数学模型;其次,为了满足工程中不同刃磨需求下摆轴回转运动的平稳性要求,解决常规PI控制无法实现此类时变系统回转速度精准控制的问题,引入了模糊控制策略对PI控制参数进行整定;最后,通过MATLAB/Simulink模块对摆轴系统进行了仿真验证。结果表明,采用模糊PI控制的摆轴系统速度跟随效果好,超调量低于1%,且具有良好的鲁棒性,能满足工程中对高精度工具磨床摆轴运动控制精度的要求。

C/C复合材料超声辅助磨削孔加工质量控制研究

为提高C/C复合材料孔加工出口边缘表面质量,以孔出口损伤因子S_(d)值(孔出口端面损伤面积与加工后理想孔面积之比)作为孔出口质量评价指标,利用单因素及正交试验方法优化磨削工艺参数,分析孔出口边缘磨削机理并提出孔出口损伤抑制策略。结果表明,当主轴转速为12000~14000 r/min,进给速度为5~7 mm/min,超声波振幅为8~9μm时,可将S_(d)值控制在4.723×10^(-3)以内。采用孔损伤抑制策略后,S_(d)值可进一步降低61.6%。此外,C/C复合材料在超声辅助磨削加工下的S_(d)值随主轴转速和超声波振幅的增加先减小后增大,随进给速度的增加逐渐增大;在保证进给速度最优时,适当提高主轴转速及超声波振幅有助于改善孔出口表面质量,并可提高加工效率。采用在临近孔出口时降低进给速度、使用刀具侧壁对孔出口进行光磨及在工件下方加设辅助支撑的策略可进一步降低孔出口损伤。

基于变刚度复杂曲面模糊路径策略的飞机座舱自动化磨抛

飞机座舱罩作为典型的复杂曲面弱刚性薄壁零件,是军用与民用飞机的重要部件,其安全与否直接关系到飞机和飞行员的安全。针对飞机座舱盖研磨抛光过程的曲面形状复杂以及刚性弱等问题,本文基于机器人自动化磨抛系统提出了一种基于自适应阻抗控制策略的复杂曲面模糊路径的生成方法,并对磨抛过程的接触力进行建模与分析,引进主被动相结合的磨抛方法,对某型飞机座舱盖进行了仿真及磨抛试验分析。试验结果表明,所提出的主被动相结合的磨抛方法结合自适应阻抗控制策略能较好的适应复杂曲面模糊路径的磨抛过程,力控制精度可达±1N;提出的复杂曲面模糊路径能够满足某型飞机座舱罩的自动化磨抛工艺需求,在保证磨抛结果一致性的同时提高了磨抛效率。

基于MRAC+PID算法的机器人打磨力跟踪控制研究

针对铝合金轮毂打磨过程中末端执行器气动系统建模不准确以及外部环境干扰导致打磨过程中打磨力稳定性差的问题,提出了一种MRAC+PID混合控制策略来实现对打磨力的跟踪控制。首先对末端执行器进行建模和分析;然后采用MRAC+PID控制策略对末端执行器进行控制,其中通过构造李雅普诺夫函数来设计自适应控制律;最后通过仿真和实验验证了所提方法的有效性。结果表明,MRAC+PID在提高系统的响应速度和抗干扰方面具有良好的控制性能,能够快速准确地跟踪期望打磨力,提高铝合金轮毂的表面打磨质量。

水泥粉磨细度控制研究进展

针对水泥辊压机终粉磨生产过程中产品颗粒过细、粒径分布窄的问题,分析辊压机粉磨数值模拟过程,探究水泥粉磨最佳粒径分布,总结水泥粉磨细度建模、粉磨过程优化和产品细度控制的国内外研究成果,认为通过建立模糊认知图模型可以解决水泥产品粒径分布不均的问题;阐述改进的比例-积分-微分控制策略、专家系统、神经网络、模糊控制等先进控制方法以及基于最优理论的模型参考自适应控制算法,并论证以上方法在水泥辊压机终粉磨过程中应用的可行性,指出模糊认知图与模型参考自适应控制相结合的控制策略可以优化水泥细粉粒径分布,提升水泥产品质量。

绳驱动并联打磨机构模糊控制策略

船舶坞修作为维护和修复船舶结构的关键环节,在船舶行业中扮演着重要的角色。然而,目前船舶坞修时表面打磨过程依赖于传统的人工作业,存在着效率低、工时长、危险性高等问题。为此,提出了一种新型绳驱动式打磨机构,该机构采用四根绳索驱动打磨装置实现三自由度的运动。首先,通过拉格朗日法建立系统的动力学模型;然后在动力学模型的基础上提出了一种带有绳索张力优化项的Fuzzy-PID(proportional integral derivative)控制策略,该控制策略可以实现精确的轨迹跟踪并保证绳索处于张紧状态;最后,通过数值仿真验证所提控制策略的有效性。结果表明,和绳牵引并联机器人上常用的PID控制相比,所提控制策略控制精度提高25%,具有较高的控制精度和稳定性。本文提出的绳驱动式打磨机构及其控制策略可为大型结构件表面处理和精密制造等应用提供一定理论支持。

刚果(金)某选矿厂磨矿优化控制专家系统研究

磨矿是选矿流程的关键作业之一,传统选矿厂通常因矿石可磨性质波动导致磨矿工艺频繁调整,相关控制参数的调整多数依赖人工经验,刚果(金)某选矿厂磨矿作业存在类似问题。本文在深入研究传统选矿厂工艺和刚果(金)选矿智能化改造和工艺控制需求后,提出了磨矿优化控制专家系统解决方案,通过磨矿工艺流程智能化控制策略对生产流程和工艺设备进行了改造,实现了磨矿过程的智能化控制和工艺分级优化,为选矿厂工艺流程优化和智能化升级提供技术方案和建设路径。

激光改性超声振动磨削制孔加工参数优化分析

为提升孔径出孔端面的品质及其控制精度,在超声振动辅助下针对硬质材料激光改性磨削孔加工参数的优化进行试验与研究。通过运用旋转超声方法,显著提高加工效率,有效克服硬脆材料孔加工难度大的问题。为评判孔出口的质量水平(Hd值),分析了孔出口端面崩边区域的范围,并实际测量了孔截面的面积比,进一步探讨了激光改性磨削工艺参数对Hd值的影响。通过试验综合分析,确定最佳的激光改性磨削工艺参数范围:主轴转速为14000~16000 r/min,进给速度为0.5~0.7 mm/min,振幅为7~8μm。与传统的激光加工相比,在最优参数下超声辅助激光改性加工后的表面质量显著提高,划痕大幅减少,显著提升了加工质量。这项研究对于提高硬质材料激光改性磨削的质量具有重要的指导意义,并易于在实际生产中推广应用。

基于机器视觉与力控的发动机弯管焊缝自动化打磨系统研究

某系列尺寸不一的弯管由2部分在中间对焊而成,目前多采用人工方式进行弯管内壁焊缝的打磨,存在打磨质量与标准不一、效率低和劳动强度大等问题。为此,设计并实现了一种基于机器视觉技术和力控的发动机弯管焊缝自动化打磨系统。利用工业相机模组正对弯管两侧端面并拍摄图像,经图像处理算法处理计算得到弯管两侧端面焊缝起始位置坐标。机械臂根据该坐标调整打磨轨迹并搭载浮动主轴,保持打磨力的恒定并对焊缝不规则区域进行补偿,实现基于位置控制和力控的打磨自适应调整。试验结果表明,系统整体打磨合格率为96.03%,相比人工打磨效率提升95.90%。系统可以在较少人工的参与和干预下完成弯管焊缝的自动化打磨,具有良好的稳定性和使用柔性,并且允许弯管存在一定的变形。

刀剪制造专用数控磨床A轴控制系统设计

针对目前刀剪磨削机床角度控制轴(A轴)传动精度低及难以实现多轴联动控制的问题,依据刀剪端面磨削工艺特点,构建出一种数控机床四轴坐标系,进行A轴机械控制机构设计,进而开发配套的数控系统,设计了A轴角度计算功能和砂轮磨损补偿功能等模块,实现A轴与机床X、Y、Z轴的四轴联动精密控制。生产实践验证,新型A轴控制系统可靠保证了刀剪磨削加工的角度精度和力矩要求,平均无故障工作时间达到30000h,刀剪的表面粗糙度达到Ra0.2μm,生产效率比现有的三轴数控磨床提高30%以上。