雷达伺服系统的自适应摩擦力矩补偿控制策略

外部扰动因素影响下,时变的摩擦扰动使得雷达伺服系统在低速跟踪扫描或成像定位跟踪时出现爬坡或停止运动等现象,严重影响了雷达系统位置跟踪精度。在雷达伺服系统的数学模型的基础上,通过试验数据分析摩擦力对伺服跟踪精度的影响。根据机载雷达伺服系统环境多变的特点,引入温度和扰动影响因子,改进LuGre动态摩擦模型,设计出自适应摩擦力矩补偿控制策略,辨识了摩擦模型的参数,并结合李雅普诺夫(Lyapunov)稳定理论进行稳定性分析,得出系统稳定的控制参数。通过对所提出的控制器进行仿真分析和试验验证,结果表明新控制器对时变的摩擦力矩具有明显的补偿作用,可以减少系统低速的爬行现象。在满足雷达系统跟踪精度要求的同时,可以有效减轻摩擦力矩对雷达伺服系统低速跟踪性能的影响。     

大型液压机驱动系统摩擦补偿控制

为提高大型液压机驱动系统控制精度,提出了基于改进型Lu Gre摩擦模型的补偿控制方法。建立了液压机驱动系统的动力学模型,通过改进型Lu Gre模型来描述液压机的综合摩擦特性。分别设计了PID控制器、2自由度PID控制器以及模糊自适应控制器,通过仿真实验验证了补偿方案的有效性,并对比分析了3种补偿控制方案的效果。仿真结果表明:采用模糊自适应补偿控制方案效果最优,2自由度PID补偿控制方案次之,常规PID补偿效果最差。当以正弦运动作为驱动系统的输入信号时,采用模糊控制补偿方案的速度跟踪均方误差(Mean Square Error,MSE)能从PID补偿方案的5.771×10-3减小至5.903×10-4。采用模糊自适应补偿方案能有效地抑制摩擦对液压机驱动系统低速性能的不利影响,可显著提高其动态跟踪性能。     

液压伺服系统的动态摩擦补偿研究

摩擦力是液压伺服系统低速性能的主要影响因素,其造成系统的低速跟踪精度和定位精度的降低.该文对阀控非对称液压缸位置控制系统进行分析并在建立摩擦力的LuGre模型基础上,提出一种基于该模型的动态摩擦补偿.最后应用实验证明了该方法的有效性.     

基于LuGre模型的气动位置伺服系统摩擦补偿控制

气动伺服系统的摩擦力/驱动之比较大,摩擦力模型复杂、受影响因素较多且存在一定的不确定性,导致精确建模比较困难;另一方面,摩擦力和气体的低刚度、弱阻尼特性相互作用导致爬行、黏滑振荡现象,严重影响了伺服系统的动态及稳态性能的提升。在综合考虑摩擦力特征、系统自身非线性、未建模动态不确定性及摩擦力和系统性能相互影响的基础上,结合LuGre摩擦模型,采用双观测器估计摩擦力模型中的部分不确定性参数,提出非线性自适应反步摩擦补偿控制方法。通过在低速和高速工况下分别进行试验验证,并与PID控制方法进行比较,结果表明非线性自适应反步摩擦补偿控制方法有效改善了起步阶段的动态滞后现象,减少了低速工况下爬行及高速工况下的黏滑振荡现象,提高系统的响应速度及跟踪精度。     

高加速度直线伺服系统高精度运动控制器设计

在中国国家自然科学基金重大项目《先进电子制造中的重要科学技术问题研究》资助下，针对先进电子制造装备中的核心问题——高加速度直线伺服系统的高精度定位控制展开研究。就高加速度直线伺服系统的高精度定位控制控制算法，高加速度直线伺服系统高精度运动控制器设计所涉及的理论研究进展提出总结报告。 针对影响系统性能的摩擦力和外部扰动，提出基于LuGre动态模型的摩擦力补偿控制、基于LuGre模型的摩擦补偿与干扰观测器相结合的控制方案、改进型干扰观测器结构(IDOB)、具有前馈控制的鲁棒内模控制结构、自适应鲁棒滑模控制算法等5种控制方案     

基于改进Dahl模型的自适应摩擦补偿研究

针对在伺服控制系统中普遍存在的摩擦现象所引起的低速爬行、跟踪误差、极限环振荡等问题,首先对伺服系统中常用的Dahl摩擦模型和LuGre摩擦模型进行了分析比较,介绍了一种改进的Dahl模型,该模型改善了摩擦环节的稳定性,并能描述滞-滑现象;然后基于Lyapunov稳定性分析的方法,设计了基于改进的Dahl模型的自适应摩擦补偿算法;最后对带有摩擦的伺服系统进行了自适应摩擦力矩补偿和PD控制补偿的仿真和实验。仿真和实验结果表明:改进的Dahl摩擦自适应补偿比PD控制补偿能更好地抑制伺服系统低速时摩擦所带来的干扰和影响,提高了定向、定位精度和系统稳定性。     

电动舵机伺服系统非线性辨识及补偿

为提高电动舵机伺服系统的跟踪精度,提出了辨识、测试它的摩擦和间隙非线性及对其进行补偿的方法.针对位置和速度双闭环控制的电动舵机伺服系统,建立了基于LuGre摩擦和迟滞间隙的数学模型;依据模型采用前馈补偿方法对系统中的摩擦进行补偿,同时采用逆模型方法对系统中的间隙进行补偿控制.实验显示,对于幅值为1°,频率为2.5Hz的给定正弦信号,补偿后系统的最大位置跟踪误差由原来的0.166°减小到了0.096°,最大速度跟踪误差由原来的2.723 r/min减小到了0.393 r/min.结果表明,本文提出的辨识测试方法能够精确地获得摩擦和间隙模型,基于该模型的补偿能够有效地提高电动舵机伺服系统的跟踪精度.     

基于修正LuGre模型的自适应鲁棒控制在机电伺服系统中的应用

机电位置伺服系统是典型的非线性系统,且存在诸多不确定性,使得传统方法设计的闭环控制器往往不能满足系统的高性能需求。针对动态摩擦参数和系统负载特性未知的情况,为伺服系统设计一种基于动态面滤波法的自适应鲁棒跟踪策略。构造一个非线性观测器来估计摩擦力矩,利用动态面滤波器简化控制器的设计,设计自适应鲁棒控制器以提高系统的稳态控制精度及鲁棒性。基于Lyapunov稳定性定理证明闭环系统的所有信号半全局一致有界,通过适当选择设计参数及初始化误差变量,跟踪误差可收敛到原点的一个任意小邻域内。仿真和试验结果表明,该控制器能够能有效地抑制摩擦干扰对伺服系统的不利影响,显著提高了系统的控制精度,为提高伺服系统的动态跟踪性能奠定基础。     

液压转台动态摩擦的自适应鲁棒补偿研究

复杂的动态非线性摩擦力矩是影响液压转台低速性能的关键因素.为提高液压转台的低速性能,通过分析液压转台单框动态摩擦力矩特性,建立转台摩擦的LuGre模型基础上,提出用一种自适应鲁棒控制补偿液压转台动态摩擦.构造两个非线性观测器对液压转台LuGre摩擦状态进行精确估计,不连续投影映射方法提高参数自适应和摩擦状态估计的稳定性,鲁棒反馈项削弱估计误差和未确定非线性以确保控制系统的鲁棒性能.对液压转台外框的试验结果证明了该方法的正确性和优越性.     

计入摩擦的进给伺服系统自适应滑模控制方法研究

针对具有非线性摩擦和有界外部扰动的进给伺服系统,设计了一种自适应滑模控制器。该控制器采用自适应算法建立了摩擦力的线性边界,将其作为滑模控制项增益,利用滑模控制项补偿摩擦和外部扰动,使系统跟踪误差渐进收敛于要求的允差内。基于Lyapunov稳定性理论证明了闭环控制系统的全局稳定性。仿真结果表明该控制器能有效补偿摩擦和外部扰动,相对于传统的PD和PID控制,显著提高了进给伺服系统的跟踪精度,并对系统参数和摩擦的不确定性具有一定的鲁棒性。     

Dynamic Friction Control Using Dynamic Structured RFNN and Friction Parameter Estimator

A nonlinear dynamic friction control is dealt with using dynamic friction observer and intelligent control.The adaptive dynamic friction observer based on the LuGre friction is proposed to estimate the friction parameters and a directly immeasurable friction state variable.The dynamic structured Recurrent Fuzzy Neural Network(RFNN)is designed to give additional robustness to the control system under the presence of the friction model uncertainty.A proposed composite control scheme is applied to the position tracking control of the servo system.The performances of the proposed friction observer and the friction controller are demonstrated by simulation.     

精密实验平台的非线性摩擦建模与补偿

非线性摩擦是影响高精度机械伺服系统动静态性能的主要因素之一。针对精密实验平台随行程位置不同表现出不同的摩擦特性,提出了一种基于LuGre模型的改进型摩擦建模方法,以速度和行程位置信号作为模型的输入变量,并用遗传算法对该模型的动静态参数进行辨识。基于改进型摩擦模型,分别通过精密实验运动平台及其相应的伺服仿真平台进行了摩擦现象和摩擦前馈补偿的实验和仿真。实验结果表明,摩擦补偿后的跟踪误差值约为补偿前的1/3,系统的静差也由原来1.4μm减小到0.4μm,与仿真平台摩擦补偿前后的现象基本一致。该改进型LuGre摩擦模型能直观、精确地描述实验平台的摩擦特性,基于该摩擦模型的前馈补偿减小了系统的跟踪误差,提高了系统的定位精度。     

High precision tracking control of a servo gantry with dynamic friction compensation

This paper is concerned with the tracking control problem of a voice coil motor (VCM) actuated servo gantry system. By utilizing an adaptive control technique combined with a sliding mode approach, an adaptive sliding mode control (ASMC) law with friction compensation scheme is proposed in presence of both frictions and external disturbances. Based on the LuGre dynamic friction model, a dual-observer structure is used to estimate the unmeasurable friction state, and an adaptive control law is synthesized to effectively handle the unknown friction model parameters as well as the bound of the disturbances. Moreover, the proposed control law is also implemented on a VCM servo gantry system for motion tracking. Simulations and experimental results demonstrate good tracking performance, which outperform traditional control approaches.     

Precision position control of servo systems using adaptive back-stepping and recurrent fuzzy neural networks

To improve position tracking performance of servo systems, a position tracking control using adaptive back-stepping control(ABSC) scheme and recurrent fuzzy neural networks(RFNN) is proposed. An adaptive rule of the ABSC based on system dynamics and dynamic friction model is also suggested to compensate nonlinear dynamic friction characteristics. However, it is difficult to reduce the position tracking error of servo systems by using only the ABSC scheme because of the system uncertainties which cannot be exactly identified during the modeling of servo systems. Therefore, in order to overcome system uncertainties and then to improve position tracking performance of servo systems, the RFNN technique is additionally applied to the servo system. The feasibility of the proposed control scheme for a servo system is validated through experiments. Experimental results show that the servo system with ABS controller based on the dual friction observer and RFNN including the reconstruction error estimator can achieve desired tracking performance and robustness.     

Robust adaptive integral backstepping control for opto-electronic tracking system based on modified LuGre friction model

This paper presents a robust adaptive integral backstepping control strategy with friction compensation for realizing accurate and stable control of opto-electronic tracking system in the presence of nonlinear friction and external disturbance. With the help of integral control term to decrease the steady-state error of the system and combining robust adaptive control approach with the backstepping design method, a novel control method is constructed. Nonlinear modified LuGre observer is designed to estimate friction behavior. Robust adaptive integral backstepping control strategy is developed to compensate the changes in friction behavior and external disturbance of the servo system. The stability of the opto-electronic tracking system is proved by Lyapunov criterion. The performance of robust adaptive integral backstepping controller is verified by the opto-electronic tracking system with modified LuGre model in simulation and practical experiments. Compared to the adaptive integral backstepping sliding mode control method, the root mean square of angle error is reduced by 26.6% when the proposed control method is used. The experiment results demonstrate the effectiveness and robustness of the proposed strategy.     

Robust sliding mode control for uncertain servo system using friction observer and recurrent fuzzy neural networks?

A robust positioning control scheme has been developed using friction parameter observer and recurrent fuzzy neural networks based on the sliding mode control. As a dynamic friction model, the LuGre model is adopted for handling friction compensation because it has been known to capture sufficiently the properties of a nonlinear dynamic friction. A developed friction parameter observer has a simple structure and also well estimates friction parameters of the LuGre friction model. In addition, an approximation method for the system uncertainty is developed using recurrent fuzzy neural networks technology to improve the precision positioning degree. Some simulation and experiment provide the verification on the performance of a proposed robust control scheme.     

Adaptive robust motion trajectory tracking control of pneumatic cylinders with LuGre model-based friction compensation

Friction compensation is particularly important for motion trajectory tracking control of pneumatic cylinders at low speed movement. However, most of the existing model-based friction compensation schemes use simple classical models, which are not enough to address applications with high-accuracy position requirements. Furthermore, the friction force in the cylinder is time-varying, and there exist rather severe unmodelled dynamics and unknown disturbances in the pneumatic system. To deal with these problems effectively, an adaptive robust controller with LuGre model-based dynamic friction compensation is constructed. The proposed controller employs on-line recursive least squares estimation（RLSE） to reduce the extent of parametric uncertainties, and utilizes the sliding mode control method to attenuate the effects of parameter estimation errors, unmodelled dynamics and disturbances. In addition, in order to realize LuGre model-based friction compensation, the modified dual-observer structure for estimating immeasurable friction internal state is developed. Therefore, a prescribed motion tracking transient performance and final tracking accuracy can be guaranteed. Since the system model uncertainties are unmatched, the recursive backstepping design technology is applied. In order to solve the conflicts between the sliding mode control design and the adaptive control design, the projection mapping is used to condition the RLSE algorithm so that the parameter estimates are kept within a known bounded convex set. Finally, the proposed controller is tested for tracking sinusoidal trajectories and smooth square trajectory under different loads and sudden disturbance. The testing results demonstrate that the achievable performance of the proposed controller is excellent and is much better than most other studies in literature. Especially when a 0.5 Hz sinusoidal trajectory is tracked, the maximum tracking error is 0.96 mm and the average tracking error is 0.45 mm. This paper constructs an adaptive robust controller     

水轮机修复专用机器人末端关节摩擦补偿

时水轮机修复机器人的末端关节,建立了包含摩擦非线性因素在内的单关节伺服模型,采用能完善描述摩擦动静态因素的LuGre模型,在MATLAB下将其转换为仿真模型,验证了补偿的有效性,机器人的响应速度、动态特性取得了满意的效果。     

考虑关键非线性特征的集成式电子液压制动系统主缸液压力精确控制

针对具有"电动机+减速机构"形式的解耦式电子液压制动系统（Electro-hydraulic brake system,EHB）展开研究。针对主缸液压力控制过程中出现的爬行、死区和振荡等问题,设计一种考虑关键非线性特征（摩擦、PV特性）的主缸液压力精确控制算法。基于LuGre模型对摩擦非线性进行补偿,设计了压力自适应控制器。针对压力闭环控制在系统死区工作点处出现的问题,采用基于死区补偿的非线性控制方法。结合以上两种方法的优点,设计基于LuGre摩擦模型前馈补偿和死区补偿的联合控制方法,能够在考虑系统关键非线性特征的基础上,精确控制主缸液压力。通过联合仿真（AMESim&Simulink）和硬件在环测试对比验证各闭环控制系统的时频域响应特性,联合控制方法提高了系统的压力动态跟踪精度和响应速度。