机床磁悬浮主轴的非线性反演自适应控制

本文研究机床磁悬浮主轴的调节问题。在分析磁悬浮主轴动力学特性的基础上,建立了其非匹配不确定性模型,在参数未知的条件下,提出了反演（Ｂａｃｋｓｔｅｐｐｉｎｇ）自适应控制的非线性设计方法,在进行参数自适应的同时实现磁悬浮主轴的鲁棒镇定。仿真结果证明了方案的有效性。     

机床磁悬浮主轴的变结构控制——Backstepping方法

本文基于机床磁悬浮主轴的非线性模型,采用反演设计的方法,提出了一种非线性的控制策略,电磁机械系统的反演变结构控制。在对主轴转子位置、速度及电流进行测量的基础上,控制器解决了主动磁主轴控制中存在的非匹配不确定性问题,实现了鲁棒镇定,仿真实例证明了控制器的有效性     

主动磁悬浮电主轴系统建模与控制参数分析

为实现磁悬浮电主轴的稳定悬浮运行并满足加工精度要求,通过对某型号主动磁悬浮电主轴的结构和控制原理进行研究,在忽略主轴转子磁化和磁漏等非线性因素影响的前提条件下,通过对主轴转子在磁悬浮轴承中的受力分析,建立了磁悬浮轴承的电磁支承力与轴承气隙偏移量及控制电流的表达式,对基于不完全微分PID控制的磁悬浮电主轴系统的临界转速与磁悬浮轴承的电磁刚度进行了定量研究,得到不同PID控制参数下,磁悬浮轴承支承刚度随涡动频率的变化曲线及固有频率随PID控制参数的变化曲线图。研究结果为磁悬浮电主轴控制系统进一步设计使用和分析优化提供了依据。     

基于恒主轴电流的机床自适应控制系统的设计

以TwinCAT3开放式数控系统为平台,设计一套恒主轴电流自适应加工系统。系统功能是在用户输入期望的目标负荷条件下,计算出合理的进给速度。首先研究机床主轴系统的力学关系以及主轴电机电流与切削负荷的关系;其次进行自适应控制系统方案的设计,采用离散非线性系统的自适应RBF控制;最后利用TwinCAT3能与Simulink进行实时通信的优点,通过搭建Simulink模型的方法实现了系统的设计,并且考虑了负荷突变的情况。最后通过具体加工,验证了系统的有效性。     

切削负载下磁悬浮电主轴系统的振动响应分析

针对切削载荷下机床加工主轴的振动响应直接影响数控机床的加工精度问题,以FGAMB公司生产的磁悬浮内螺纹铜管加工主轴为研究对象,通过建立该磁悬浮加工主轴的动力学模型结合切削载荷下主轴的振动响应模型,基于ANSYS Workbench软件对磁轴承-转子系统进行了模态分析,从而计算出前6阶的固有频率和主振型,进而通过谐响应分析,确定了加工过程中主轴系统所受激振力的危险频率范围和幅频特性,得出主轴系统发生共振时可能产生的最大振动幅值。仿真结果表明,当工件满足GB/T 20928-2007加工精度要求时,激振力的频率应控制在[224,680]Hz,加工速度控制在[13440,40800]r/min。     

磁悬浮直线导轨悬浮高度的自适应积分滑模控制

介绍磁悬浮直线导轨这一新型机电进给装置。针对该装置悬浮部分复杂非线性、参数时变、强扰动的特点,应用自适应积分滑模控制方法设计磁悬浮系统恒悬浮高度控制器。自适应积分滑模控制器可以在线实时估计不确定系统的边界值,削弱滑模控制的抖振,减小稳态误差。与PID控制器的仿真对比实验表明,自适应积分滑模控制器具有更好的动、静态特性和鲁棒性。     

用于主轴热控制的水冷机设计

为了有效抑制机床主轴发热，降低主轴热对机床精度的影响，提出一种用于主轴热控制的水冷机设计方法。根据机床主轴内部热源分布特点，制定机床水冷机的总体设计方案，并开发各功能子模块，在对水冷过程进行功能分析的基础上，提出机床水冷机的控制原理与方法。实验研究表明:机床水冷机可使主轴温度降低30%，热平衡时间缩短45%。     

专用数控机床主轴早期可靠性控制图分析

数控机床主轴早期可靠性研究是数控机床可靠性研究的关键组成部分。通过对数控机床主轴早期故障实验前采集的主轴变形数据的分析，建立了早期可靠性变形控制图，用来监控主轴早期可靠性。根据对数据的分析，判断主轴是否存在故障，进而在不损坏机床主轴的前提下，消除主轴早期故障，提高机床可靠性。     

基于微分平坦的磁悬浮移动平台控制研究

由于磁悬浮移动平台具有强非线性，目前各类智能算法只能对磁悬浮移动平台进行定位移动，并不能使磁悬浮移动平台的动子沿着期望轨迹到达预定位置。为了解决磁悬浮移动平台动子的轨迹跟踪及其精准性等问题，将微分平坦理论与磁悬浮移动平台控制相结合。磁悬浮移动平台系统是微分平坦系统，而微分平坦理论具有特殊性，可以将强非线性系统转化为线性系统后进行控制。搭建磁悬浮移动平台的数学模型，在MATLAB/Simulink中进行仿真。结果表明：微分平坦控制的磁悬浮移动平台能够使其动子按照期望轨迹进行运动，且精度更高、跟踪性更强，具有实用性。     

光控技术在组合机床主轴定位中的应用

介绍了利用光电脉冲与ＰＬＣ结合作为控制单元，控制制动器达到主轴定区域定位，代替利用定位电机给主轴定位的老方法。从而降低了组合机床的生产成本，提高了机床加工的可靠性，同时也提高了母机的工作效率。     

电液位置伺服系统的模糊CMAC神经网络控制研究

本文提出了一种模糊ＣＭＡＣ神经网络的结构和算法。该网络通过权系数的在线学习,实现修正模糊逻辑。将此网络作为前馈补偿单元,与ＰＤ控制器一志构成一种自学习控制器,并对带有未知负载干扰的某电液位置系统进行动态仿真。结果表明,该控制器具有强的鲁棒性以及良好的跟踪特性。     

Direct adaptive control of end milling process

A direct adaptive control algorithm, which is spindle speed and drive dynamics independent, has been developed for machining operations. The combined dynamics of feed motion and cutting process are modelled as a third order system whose parameters may vary with spindle speed and part geometry changes during machining. The algorithm does not use any specific time interval, thus sampling time dependent discrete transfer functions and pole assignments are avoided. The adaptive controller is designed to have a closed loop characteristic function which behaves like an open loop regular and stable machining operation. The proposed direct adaptive controller is practical, can be used in any multi-axes machining, and can be combined with chatter suppression techniques which require spindle speed regulation. The algorithm is applied to the adaptive control of milling. Satisfactory results are obtained in constraining the maximum cutting forces and dimensional surface errors in milling experiments.     

基于反步控制的非线性干扰观测器的外部不确定干扰的电液位置伺服系统

由于电液系统中存在各种非线性因素以及不确定干扰,为提高电液位置伺服系统在干扰下的控制精度,以电液振动台为控制对象,建立非线性模型,利用干扰观测器对干扰力进行观测,并通过反步控制器进行削弱和补偿,利用李雅普诺夫理论保证闭环系统的全局稳定.对设计的控制器进行仿真和实验,模拟在有外界未知干扰力下的位置控制,实现对干扰的抑制.实验表明:该控制策略能够很好的提高电液位置伺服系统的跟踪性能.     

The improvement of thermal error modeling and compensation on machine tools by CMAC neural network

In this paper, a cerebellar model articulation controller (CMAC) neural network is proposed for thermal error modeling in machine tools. The CMAC is a systematic learning algorithm which can search for the nonlinear and interaction characteristics between the thermal errors and temperature field on the machine tools. The CMAC is investigated in terms of accuracy in prediction, robustness to sensor placement, speed of learning, and tolerance to sensor failures. Experimental measurements of the spindle drift errors for both a horizontal machining center and a CNC turning center were performed using capacitance sensors and thermal sensors. Results show that the CMAC model has better performance than other modeling methods in robustness to sensor placement and speed of learning. This makes determination of the sensor locations easier, and reduces calibration time. In addition, a sensor failure detection algorithm is developed to provide better reliability.     

Chatter suppression by adaptive speed modulation

In this paper a PD fuzzy logic controller is designed and implemented to suppress chatter in peripheral milling. The controller selects combinations of the amplitude and frequency of spindle speed modulation, online, to keep a chatter indicator, the R-value, close to a prescribed set point. The controller was successful in suppressing chatter at certain operating points. The effect of the control action delay time and the degree of process instability on the controller performance were addressed through simulations and experiments. At some operating points the controller resulted in an oscillatory behaviour of the process and the R-value fluctuated significantly. Stability lobes were used to explain this phenomenon. Strategies for enhancing the performance of the controller were proposed.     

数控伺服进给系统中的非线性预测控制

在分析数控加工过程中进给伺服系统的非线性摩擦力因素的基础上，提出了位置环非线性预测控制器设计方案。该控制器采用了RBF神经网络实现预测模型及其在线校正，黄金分割法进行滚动优化计算。并在Matlab环境下进行了仿真，实验结果表明，预测控制器能有效地改善系统控制质量，抑制非线性摩擦力带来的不利影响。     

基于神经网络的变量泵模型跟踪控制

本文用神经网络逼近对象的非线性逆模型,通过神经网络模型参考控制实现电液比例斜盘倾角和流量的控制,使系统的不确定性和非线性等得到补偿。仿真和实验表明,所开发的神经网络控制器能够较好地实现VDAPP控制,有较好的自适应性和鲁棒性,跟踪性能有较大改善。     

Friction characterization and compensation of a linear-motor rolling-guide stage

In this article, characterization and compensation for the friction at the micro (plastic module and nonlinear spring) and macro modes (nonlinear Coulomb and Stribeck) of a linear-motor rolling-guide stage are reported. Because the system dynamics under the micro and macro modes are very different, the paradox to determine the optimal servo gains for both modes was solved by a two-stage fuzzy PID controller. The fuzzy PID controller possesses a switching mechanism that continuously tunes the servo gains according to the system states. For the precision reversal path tracking at low speed, the system dynamics is dominated by the complicated and nonlinear friction characteristics. Due to the nonlinear spring characteristics, the friction was found unsymmetrical at the reversal points of the low speed path tracking. A simplified unsymmetrical friction model was proposed and proved to improved motion precision well. From the simulations and experiments, the proposed controller shows good tracking and positioning accuracy after friction compensation.