Position regulator for spindle of milling machine by embedded magnetic bearings

The goal of this work is to concurrently counter-balance the dynamic cutting force and regulate the spindle position deviation by integrating active magnetic bearing (AMB) technique, fuzzy logic algorithm and an adaptive self-tuning feedback loop. The mathematic model for cutting dynamics is constructed by experiments so that the system parameters can be on-line estimated by employing the proposed fuzzy logic algorithm. Once the cutting force can be real-time estimated, the corresponding compensation force can be exerted by the equipped AMB to counter-balance the cutting force (i.e., via inner-loop), in addition to the spindle position regulation by the feedback of spindle position (i.e., via outer-loop). At the end, the experimental simulations on realistic milling are presented to verify the efficacy of the fuzzy controller for spindle position regulation and the capability of the dynamic cutting force counterbalance.     

基于神经网络补偿的转台伺服系统控制研究

针对飞行仿真转台伺服系统中存在的非线性摩擦干扰进行了研究,采用一种基于RBF神经网络进行误差补偿的在线自适应控制策略。在基于逆动力学的计算力矩控制方法的基础上,利用RBF神经网络的万能逼近特性在线辨识模型误差,从而对系统进行补偿,其权值自适应律根据Lyapunov稳定性理论推导,保证了系统跟踪误差的收敛及稳定,仿真结果表明该控制策略可使位置MAE指标从0.0087m提高到0.0016m,使位置MSE指标从1.0128e-4m提高到3.3002e-6m,具有较高的鲁棒性和稳态控制精度。最后分别从隐层节点数及节点中心学习算法的变化两方面提出两种改进方案,仿真结果表明隐层节点数的增加可以进一步减小位置误差,而采用K-means均值聚类算法解决了神经网络节点中心按经验选取或试凑的困难。     

基于柔性人机接口的人机协调运动控制方法

为改善基于力信息的人机协调运动中人机交互力,采用了在人机接口中设置弹性元件的方法,建立了具有柔性人机接口的人机交互力学模型。在已有鲁棒自适应阻抗控制方法的基础上进行改进,提出了一种基于柔性人机接口的自适应阻抗控制方法。此控制方法是对阻抗外环位置速度进行比例补偿,对力控制内环采用模糊PID (proportion integral differential)控制,实现改进自适应阻抗算法,从而提高了位置跟随精度,并有效减小了人机交互力。分析了人机接口中弹性元件对控制效果的影响,获得了不同刚度系数时,交互力控制效果和位置跟随精度。在此基础上,建立了试验系统,完成了试验。人机协调运动试验结果显示：应用柔性人机接口和改进后的控制方法具有更好的人机交互力控制效果。标准运动输入试验结果显示：改进后的控制方法具有更好的人机交互力控制效果和更高的位置跟随精度;人机交互力大小、位置跟踪准确性与人机接口刚度系数大小均成正比。     

变摩擦力下板带轧机垂扭耦合振动控制技术

当前对板带轧机垂扭耦合振动的控制过程未考虑变摩擦力的影响，无法对振动特性进行准确分析，导致控制效果不理想。提出一种变摩擦力下基于振动摩擦模型的板带轧机垂扭耦合振动控制技术。将垂扭耦合振动参数作为输入向量，理想状态下变摩擦力作为输出向量，确定垂扭耦合振动参数。采用遗传算法对已确定的最优垂扭耦合振动参数进行辨识，构建振动摩擦模型，完成对垂扭耦合振动特性的准确分析，解决控制过程中的变摩擦力影响问题。利用振动摩擦模型对系统位移响应和频域响应振动特性进行控制，实现板带轧机垂扭耦合振动的控制。与传统控制技术进行对比，得出实验结果，所提控制技术控制精度可达98%，能够减小控制过程的变摩擦影响，可对振动特性进行准确地准确分析，大大提高了控制精度。     

Desired Compensation Adaptive Robust Control of Electrical-optical Gyro-stabilized Platform with Continuous Friction Compensation Using Modified LuGre Model

Continuous friction compensation along with other modeling uncertainties is concerned in this paper, to result in a continuous control input, which is more suitable for controller implementation. To accomplish this control task, a novel continuously differentiable nonlinear friction model is synthesized by modifying the traditional piecewise continuous LuGre model, then a desired compensation version of the adaptive robust controller is proposed for precise tracking control of electrical-optical gyro-stabilized platform systems. As a result, the adaptive compensation and the regressor in the proposed controller will depend on the desired trajectory and on-line parameter estimates only. Hence, the effect of measurement noise can be reduced and then high control performance can be expected. Furthermore, the proposed controller theoretically guarantees an asymptotic output tracking performance even in the presence of modeling uncertainties. Extensively comparative experimental results are obtained to verify the effectiveness of the proposed control strategy.

     

Delay time compensation based on coefficient of restitution for collision hybrid motion simulator

A hybrid motion simulator embeds a hardware experiment in a numerical simulation loop. However, it is often subjected to the inherent problem of an energy increase in the collision of two pieces of hardware in a loop because of the delay time. This paper proposes a delay time compensation method based on contact dynamics model for a collision hybrid motion simulator under delay time and establishes a compensation method for coupled translational and rotational motion. The model developed in this paper describes linear uniform motion of a floating object during the period of the delay time until the force and torque are observed and non-linear motion according to environmental stiffness after the initial delay time period in contact. By using the above model, compensation parameters are designed based on desired coefficient of restitution with iterative calculation. The proposed method achieves accurate delay time compensation and simultaneously realizes a variable desired coefficient of restitution over a wide range of frequencies. Furthermore, the compensation method for multi-dimensional motion is established under the assumption that the friction effect is very small. The efficiency of the proposed method is verified through collision experiments for the coupled motion in two dimensions.     

再磨过程的泵池液位和给矿压力双速率区间控制

赤铁矿再磨过程是以矿浆泵频率为输入、以给矿压力为内环输出、以泵池液位为外环输出的强非线性串级工业过程.当赤铁矿粒度分布大范围变化,导致一段磨矿与磁选矿浆流量和再磨排矿流量频繁波动,使泵池液位频繁波动,造成内外环频繁波动.本文将上述动态特性变化用未建模动态来描述,通过设计消除前一时刻未建模动态补偿信号叠加于基于线性模型设计的反馈控制器,采用一步最优前馈控制律和提升技术,提出了泵池液位和给矿压力双速率区间控制算法.给出了所提控制算法的稳定性和收敛性分析,通过半实物仿真实验表明所提出的控制算法可以将处于频繁随机波动的泵池液位和给矿压力变化率控制在目标值范围内.     

基于数据挖掘与系统理论建立摩擦模糊模型与控制补偿

建立机械摩擦力模型及其相应的控制补偿策略一直是人们所关注的问题. 由于摩擦力所固有的非线性及不确定特征, 用传统的数学建模与控制补偿方法难以达到满意的系统性能要求. 本文采用模糊建模技术逼近摩擦动力系统并将辨识结果用在前馈补偿控制器设计中. 模糊建模过程由以下3个部分组成: 首先采用数据挖掘技术辨识出模糊系统的模糊规则库, 然后利用该规则库建立模糊系统的静态模型, 最后以李雅普诺夫稳定性理论为基础进一步辨识出模糊系统的动态模型. 在控制器设计方面, 采用了自适应模糊系统前馈补偿的比例微分(Proportional-derivative, PD)算法. 运用李雅普诺夫稳定性分析证明了闭环系统跟踪误差的有界性. 数值仿真结果表明了该方法的有效性和实用性.     

基于干扰补偿的拦截弹制导控制一体化设计

针对姿控式直接力/气动力复合控制拦截弹,提出一种基于干扰补偿和动态面方法的制导控制一体化(IGC)算法.首先设计一种适用于未知上界干扰的变增益扩张状态观测器(TVGESO),在有效保证估计精度的同时,能够减弱初始尖峰现象;然后考虑目标机动以及喷流扰动等模型不确定性,应用TVGESO在线干扰逼近补偿,基于积分滑模动态面方法设计了IGC算法;最后基于Lyapunov理论对闭环系统稳定性进行证明.数值仿真结果表明了所提出设计方案的有效性.     

Decentralized adaptive fuzzy control of robot manipulators

This paper develops a decentralized adaptive fuzzy control scheme for robot manipulators via a combination of genetic algorithm and gradient method. The controller for each link consists of a feedforward fuzzy torque-computing system and a feedback fuzzy PD system. The feedforward fuzzy system is trained and optimized off-line by an improved genetic algorithm, that is to say, not only the parameters but also the structure of the fuzzy system are self-organized. Because genetic algorithm can operate successfully without the system model, no exact inverse dynamics of the robot system are required. The feedback fuzzy PD system, on the other hand, is tuned on-line using gradient method. In this way, the proportional and derivative gains are adjusted properly to keep the closed-loop system stable. The proposed controller has the following merits: (1) it needs no exact dynamics of the robot systems and the computation is time-saving because of the simple structure of the fuzzy systems; and (2) the controller is insensitive to various dynamics and payload uncertainties in robot systems. These are demonstrated by analyses of the computational complexity and various computer simulations.