Robust tracking control for micro machine tools with load uncertainties

The quality of the micro-mechanical machining outcome depends significantly on the tracking performance of the miniaturized linear motor drive precision stage. The tracking behavior of a direct drive design is prone to uncertainties such as model parameter variations and disturbances. Robust optimal tracking controller design for this kind of precision stages with mass and damping ratio uncertainties was researched. The mass and damping ratio uncertainties were modeled as the structured parametric uncertainty model. An identification method for obtaining the parametric uncertainties was developed by using unbiased least square technique. The instantaneous frequency bandwidth of the external disturbance signals was analyzed by using short time Fourier transform technique. A two loop tracking control strategy that combines the μ-synthesis and the disturbance observer (DOB) techniques was proposed. The μ-synthesis technique was used to design robust optimal controllers based on structured uncertainty models. By complementing the μ controller, the DOB was applied to further improving the disturbance rejection performance. To evaluate the positioning performance of the proposed control strategy, the comparative experiments were conducted on a prototype micro milling machine among four control schemes: the proposed two-loop tracking control, the single loop μ control, the PID control and the PID with DOB control. The disturbance rejection performances, the root mean square (RMS) tracking errors and the performance robustness of different control schemes were studied. The results reveal that the proposed control scheme has the best positioning performance. It reduces the maximal errors caused by disturbance forces such as friction force by 60% and the RMS errors by 63.4% compared with the PID control. Compared to PID with DOB control, it reduces the RMS errors by 29.6%.     

Parameter identification of inertially stabilized platforms using current command design

Accurate parameter identification is essential when designing controllers for inertially stabilized platforms (ISPs). But traditional identification methods suffer from observation measurement noise and operating restrictions of ISPs. To address this issue, a novel identification method based on current command design and multilevel coordinate search (MCS) algorithm without any higher order measurement differentiations was proposed. The designed current commands were adopted to obtain parameter decoupled models with the platform operating under allowable conditions. MCS algorithm was employed to estimate the parameters based on parameter decoupled models. A comparison experiment between the proposed method and non-linear least square method was carried out and most of the relative errors of identified parameters obtained by the proposed method were below 10%. Simulation and experiment based on identified parameters were conducted. A velocity control structure was also developed with disturbance observer (DOB) for application in disturbance compensation control system of an ISP. Experimental results show that the control scheme based on the identified parameters with DOB has the best disturbance rejection performance. It reduces the peak to peak value (PPV) of velocity error integral to 0.8 mrad which is much smaller than the value (10 mrad) obtained by the single velocity controller without DOB. Compared with the control scheme based on sweep model with DOB compensation, the proposed control scheme improves the PPV of velocity error integral by 1.625 times.     

摩擦对稳定跟踪平台低速性能影响的研究

以某型直升机驾驶员夜视系统稳定跟踪平台伺服系统设计为背景，针对系统中存在的非线性摩擦影响，着眼于摩擦模型、二质量伺服系统模型以及摩擦补偿问题，从理论上进行了探讨。     

光电稳定跟踪装置中微机电陀螺应用研究

以微机电陀螺在高精度光电稳定跟踪装置中的应用为背景,研究了陀螺输出噪声对光电稳定跟踪平台精度的影响.结果表明,陀螺噪声会引起平台基准轴的抖动和缓慢漂移.根据微机电陀螺的实测数据,分析了其噪声特性.基于AR模型建立了微机电陀螺的噪声统计模型.研究了基于Kalman滤波的陀螺去噪算法,给出了去噪结果,分析了该算法不能够取得较好滤波效果的原因.针对Kalman滤波在微机电陀螺信号低频去噪方面的局限性,将基于阈值决策的小波去噪方法应用于微机电陀螺的信号处理中,给出了滤波结果.实测结果表明由于后者不依赖于噪声的精确模型,可根据噪声在不同频段的统计特性采用阈值决策滤波,具有更好的抑噪效果.最后给出了两种滤波算法的比较.     

稳定平台中通用陀螺数据采集处理系统

为提高稳定平台的性能,针对平台中各种类型陀螺高速度、高精度、宽动态范围的设计指标要求,研制了一种通用数据采集处理系统。在详细分析动力调谐、光纤和微机械陀螺典型型号性能参数指标的基础上,提出了系统的设计指标要求,选择8通道24位∑-？高精度模数转换器ADS1278和32位数字信号处理器TMS320F2812,设计实现系统的硬件电路,编写了相关的软件程序,并进行了实验验证。实验表明：系统的转台测试数据与陀螺出厂标定的性能参数之间,测量误差小于1%,完全满足稳定平台中陀螺的应用要求。     

三轴磁罗盘的高精度误差补偿算法研究

介绍了倾斜补偿下三轴磁航向测量的基本原理,分析了航向误差的形成原因.根据罗差分解和正交修正基准轴的概念,本文提出了一种基于二次正交修正的高精度磁航向误差补偿算法,该方法具有补偿精度高,算法简单等优点.文章给出了该算法应用于HMR2300型磁罗盘进行航向测量的实验结果,说明了该算法的可行性和有效性.     

光电伺服控制系统多回路内模控制器分析与设计

针对光电稳定平台中伺服控制系统的模型不确定性、内外部扰动和传感器误差等各项因素,提出基于多回路、双自由度内模控制的稳定环控制器设计方法,实现对各项误差因素的控制器分层设计.首先,对伺服控制系统的单回路控制结构和多回路内模控制结构进行描述,并深入分析了两者的误差扰动和模型扰动抑制性能;然后,详细讨论了多回路内模控制结构中...     

分布式电驱车路径跟踪分层协调控制方法研究

针对分布式电驱车路径跟踪问题,基于分层协调控制方法,提出了一种路径跟踪策略。由电驱车独立转向/驱动的结构优势,设计四轮阿克曼转向理论,以建立电驱车路径跟踪分层运动学模型,并应用到路径跟踪控制策略中。该策略分为上下两层控制。在上层控制中,将上层运动学模型作为模型预测控制算法的预测模型,通过设定最优目标函数和约束条件将未来控制增量的求解问题转换为二次规划的最优解问题,计算出最优转角和速度控制量。下层控制中,通过下层运动学,将上层控制得到的控制量映射到四轮的转角和速度控制量,应用模糊PID算法,实现电驱车的路径跟踪控制。在基于Carsim/Simulink的仿真平台上进行圆形路径跟踪仿真验证,结果表明,该控制器能够使分布式电驱车实现路径的准确跟踪;在实车试验中进行换道路径跟踪,简单MPC(模型预测控制算法)与分层协调控制数据结果对比表明分层协调控制方法能够有效的改善控制性能,提供路径跟踪的精确性和稳定性。     

适合PVC企业转产的高附加值氯氢产品

重点介绍三氯乙烯、CPVC、EPVC及综合塑料加工项目的市场、技术及发展前景,这些产品和项目适合PVC企业转产。     

基于模糊加权EKF的车载光电桅杆姿态估计算法

针对车载桅杆式光电探测平台静动态情况下的姿态测量问题,提出了一种基于模糊加权的姿态估计算法.首先采用欧拉角法描述姿态运动学方程,并在详细分析陀螺和倾角仪数学模型的基础上,推导出系统的非线性连续状态空间模型;然后采用EKF对系统进行线性化和离散化,并在卡尔曼滤波框架下,提出姿态角和陀螺漂移的加权量测更新方程;最后通过分析...