Adaptive Robust Servo Control for Vertical Electric Stabilization System of Tank and Experimental Validation

A tracking stability control problem for the vertical electric stabilization system of moving tank based on adaptive robust servo control is addressed.This paper mainly focuses on two types of possibly fast timevarying but bounded uncertainty within the vertical electric stabilization system:model parameter uncertainty and uncertain nonlinearity.First,the vertical electric stabilization system is constructed as an uncertain nonlinear dynamic system that can reflect the practical mechanics transfer process of the system.Second,the dynamical equation in the form of state space is established by designing the angular tracking error.Third,the comprehensive parameter of system uncertainty is designed to estimate the most conservative effects of uncertainty.Finally,an adaptive robust servo control which can effectively handle the combined effects of complex nonlinearity and uncertainty is proposed.The feasibility of the proposed control strategy under the practical physical condition is validated through the tests on the experimental platform.This paper pioneers the introduction of the internal nonlinearity and uncertainty of the vertical electric stabilization system into the settlement of the tracking stability control problem,and validates the advanced servo control strategy through experiment for the first time.

Robust visual servoing based Chinese calligraphy on a humanoid robot

A robust visual servoing system is investigated on a humanoid robot which grasps a brush in Chinese calligraphy task.The system is implemented based on uncalibrated visual servoing controller utilizing Kalman-Bucy filter,with the help of an object detector by continuously adaptive MeanShift(CAMShift) algorithm.Under this control scheme,a humanoid robot can satisfactorily grasp a brush without system modeling.The proposed method is shown to be robust and effective through a Chinese calligraphy task on a NAO robot.

Study of Dynamic Robustness of Servo Control System on a Water Press

The reliability and robustness of the electro-hydraulic servo control system for heavy-duty forging machine play an important role in forging processes. A mathematic model of 50 MN water press for free forging was created in this research. The dynamic robust compensator integrating with PID control method is designed and applied to the mathematical model simulation. The simulated results approved that the dynamic robust compensator application restrains interference from extra load and improves the electro-hydraulic position servo control system accuracy and stability.

高压气动压力伺服系统的鲁棒控制

高压气动压力伺服系统的参数不确定性和未建模动态制约了其控制精度的提高,针对此提出了基于RISE的自适应鲁棒控制算法用于高压气动压力伺服系统的控制。考虑到核心元件高压电气伺服阀的控制性能对高压气动压力伺服系统高精度控制的影响,设计了交叉对比实验,实验结果表明,伺服阀位置控制算法有助于避免正弦信号失真、减小稳态压力抖动,系统压力控制算法能提高系统的响应速度和动态跟踪能力。

基于H_(∞)控制器的阀控非对称缸位置伺服系统控制

以阀控非对称缸位置伺服系统为研究对象,建立其数学模型;针对负载突变及油液弹性模量变化提出了H∞鲁棒控制方法,从频域上分析了控制器对系统动态性能和稳态性能的影响。采用AMESim和MATLAB/Simulink搭建了阀控非对称缸位置伺服系统的联合仿真模型,对不同工况下控制器的跟踪精度及抗扰能力进行仿真研究。最后,通过油缸加载实验测试平台对仿真结果进行进一步验证。结果表明:所设计的H∞控制器提高了系统的快速性和鲁棒性,相比于PID控制下系统正弦响应结果,H∞控制器的最大跟踪误差在无负载工况下降低了48.8%,在负载突变工况下降低了56.25%;同时阶跃响应时间缩短了7.5%。

基于反步鲁棒控制的伺服系统抗风扰策略

针对大型天线定向能发射武器系统容易受到风扰影响导致控制性能下降的问题,提出了一种反步鲁棒控制策略。首先,分析了风扰的构成,对占主导的阵风力矩进行了建模;然后,改进了反步控制器,加入基于符号函数的新型鲁棒控制项,在适用于阶跃响应的同时有效抑制了非线性随机力矩的影响;最后,通过仿真实验和结果分析,证明了反步鲁棒控制策略的快速性和稳定性优于反步控制策略。

基于鲁棒自适应的减震阻尼器试验台加载位移跟踪控制

减震阻尼器是用于建筑、桥梁、风电、管道等领域减震的核心零部件,减震阻尼器试验台是测试减震阻尼器动/静态特性的试验装置。针对减震阻尼器试验台在位移加载时实际位移与期望位移跟踪误差较大的问题,建立试验台液压伺服位移控制系统数学模型,设计鲁棒自适应控制器,并基于李雅普诺夫理论验证控制器的稳定性,提出一种基于鲁棒自适应的位移跟踪控制方法。搭建Simulink与AMESim联合仿真模型,对试验台电液伺服系统的控制方法进行仿真分析;搭建试验台并对比验证鲁棒自适应控制器与传统PID控制器的控制性能。结果表明:鲁棒自适应控制器具有较强的抗干扰能力,跟踪误差较PID控制器减少了55%,响应速度提高了66.7%,较大程度提高了试验台加载系统的位移跟踪控制精度。

未知干扰下电液伺服系统模型预测控制

电液伺服系统采用阀控双出杆液压缸的数学模型,针对系统的非线性、不确定性与未知干扰等问题,提出一种基于干扰观测器的模型参数变化的模型预测控制方案。为了处理阀控双出杆液压缸负载流量系统非线性特性和负载压力时变的问题,采用预测模型时变的模型预测控制策略。把系统建模误差、未建模摩擦不确定性和外界扰动作为系统混合未知干扰,对混合干扰采用指数收敛干扰观测器进行在线观测,观测结果对预测模型进行实时补偿。仿真结果表明,所提方法对干扰和不确定性有很好的鲁棒性,具有较高的控制精度。

基于ATSMC的破障武器随动系统控制研究

针对电动缸驱动的车载破障武器随动系统控制问题,提出了一种基于指数收敛的干扰观测器和反正切滑模控制器的方法。研究了电动缸传动时系统具有的非线性增益,推导了电动缸机构的变传动比和变负载力矩的公式。为了对随动系统进行位置和速度控制,根据多项式Terminal滑模控制器的思想,采用等效趋近律的方法,设计了反正切Terminal滑模控制器(ATSMC),其具有全局鲁棒性和有限时间可达的能力;为了对系统内部的不确定性和外部扰动进行观测和补偿,设计了一种基于指数收敛的干扰观测器。对控制系统进行仿真,结果表明,ATSMC具有更好的鲁棒性,提高了随动系统控制精度,缩短了响应时间;基于指数收敛的干扰观测器能较好地补偿系统运行中产生的各种扰动,降低了系统稳态误差。

数控机床伺服驱动系统的多电机同步控制策略

以数控机床伺服驱动系统的多电机同步控制为研究对象,提出了一种基于多交流伺服电机的同步控制策略。此策略将虚拟主轴和偏差耦合的同步控制方式相结合,并加入反向传播神经网络比例积分微分控制以及自适应鲁棒控制。通过搭建Matlab/Simulink仿真平台模拟了系统的运行状态。结果表明,所提同步控制策略具有良好的同步性能和伺服效果,在提高多电机联动系统的控制精度和响应速度、减少摩擦和齿隙的影响以及增强系统鲁棒性方面表现出优越性。

Adaptive Robust Tracking Control of Pressure Trajectory Based on Kalman Filter

When adaptive robust control（ARC） strategy based on backstepping design is applied in pneumatic servo control, accurate pressure tracking in motion is especially necessary for both force and position trajectories tracking ofrodless pneumatic cylinders, and therefore an adaptive robust pressure controller is developed in this paper to improve the tracking accuracy of pressure trajectory in the chamber when the pneumatic cylinder is moving. In the proposed adaptive robust pressure controller, off-line fitting of the orifice area and on-line parameter estimation of the flow coefficient are utilized to have improved model compensation, and meanwhile robust feedback and Kalman filter are used to have strong robustness against uncertain nonlinearities, parameter fluctuations and noise. Research results demonstrate that the adaptive robust pressure controller could not only track various pressure trajectories accurately even when the pneumatic cylinder is moving, but also obtain very smooth control input, which indicates the effectiveness of adaptive model compensation. Especially when a step pressure trajectory is tracked under the condition of the movement of a rodless pneumatic cylinder, maximum tracking error of ARC is 4.46 kPa and average tracking error is 0.99 kPa, and steady-state error of ARC could achieve 0.84 kPa, which is very close to the measurement accuracy of pressure transducer.

Enhancing Design of Visual-Servo Delayed System

A robust adaptive predictor is proposed to solve the time-varying and delay control problem of an overhead crane system with a stereo-vision servo. The predictor is based on the use of a recurrent neural network(RNN) with tapped delays, and is used to supply the real-time signal of the swing angle. There are two types of discrete-time controllers under investigation, i.e., the proportional-integral-derivative(PID) controller and the sliding controller. Firstly, a design principle of the neural predictor is developed to guarantee the convergence of its swing angle estimation. Then, an improved version of the particle swarm optimization algorithm, the parallel particle swarm optimization(PPSO) method is used to optimize the control parameters of these two types of controllers. Finally, a homemade overhead crane system equipped with the Kinect sensor for the visual servo is used to verify the proposed scheme. Experimental results demonstrate the effectiveness of the approach, which also show the parameter convergence in the predictor.

Zero phase error control based on neural compensation for flight simulator servo system

Using the future desired input value, zero phase error controller enables the overall system＇s frequency response exhibit zero phase shift for all frequencies and a small gain error at low frequency range, and based on this, a new algorithm is presented to design the feedforward controller. However, zero phase error controller is only suitable for certain linear system. To reduce the tracking error and improve robustness, the design of the proposed feedforward controller uses a neural compensation based on diagonal recurrent neural network. Simulation and real-time control results for flight simulator servo system show the effectiveness of the proposed approach.

TRACKING VARIABLE STRUCTURE CONTROL LAW WITH APPLICATION TO ELECTRO－HYDRAULIC SERVO SYSTEMS

Combining the characteristics of servo systems , tracking variable structure control law is studied. Two kinds of new variable control law , the generalized exponential approaching vari- able structure control law and the integral variable structure control law are put forward for dis- crete time domain. Taking pump-controlled-motor rotational speed servo system for example , the experiment investigation and digital simulation of integral variable structure control law for dis- crete time domain are performed , the rightness of conclusions are verified.

LMI Approach to Robust H_∞/H_2 Controller Design with Regional Poles Constraint of a Pump-Motor System

The time domain guideposts requirements of a pump-motor system is transfered into a series of constraints which express the robust performance upper bound and regional poles limits of the closed loop system. Then the servo system control problem is transferred into the problem of robust performance optimizing under regional poles constrains described by linear matrix inequality （LMI）. These LMIs are easy to solve through the Matlab LMI-toolbox. Simulations indicate that the controller has excellent dynamic, static and disturbance rejection performance, and the control system is robust and has perfect H2 performance to the bounded external torque disturbance.

双阀气动伺服系统的LuGre摩擦模型补偿研究

由于摩擦会引起气动位置伺服系统的动态滞后,尤其是气缸活塞在换向过程中容易产生"平顶"现象,因此需要对气动系统进行摩擦补偿。但是由于气动系统本身的参数不确定性和强非线性会影响摩擦补偿的效果,同时气缸两腔耦合与流量饱和会导致控制系统的自由度不高且能量损失较大。针对以上问题,文中采用表征摩擦动态特性良好的LuGre模型来描述气缸摩擦并提出了一种自适应鲁棒控制器进行摩擦补偿,控制器的自适应部分用于控制参数不确定性,鲁棒控制部分用来处理系统的非线性。同时采用两个三位四通比例阀来提高控制自由度并降低能量耗散。仿真结果表明:该补偿策略有效改善了摩擦带来的动态滞后,提高了系统的响应速度与跟踪精度。

航天伺服机构鲁棒控制与机电液联合仿真

航天伺服机构设计对于航天器的控制而言具有重要作用,其控制算法的研究与仿真模拟平台的搭建具有重要的实用价值。针对航天伺服机构的机械、电、液压等环节完成仿真建模,完成了伺服机构的整体模型建立。在ADAMS中进行了伺服机构的机械结构搭建,使用AMESim完成了液压模块的搭建,并采用H∞理论设计了鲁棒控制器,利用Matlab工具箱完成了控制器的构建。结合ADAMS、AMESim的动力学模型,联合Matlab控制器模型,实现了各部分模块的联合仿真。通过联合仿真技术完成了对实物系统更加真实的模拟,并且更直观地展现了实验结果,对于实际航天伺服机构系统的设计和搭建而言具有重要的指导意义。

软体机械臂水下自适应鲁棒视觉伺服

水下仿生软体机器人在水底环境勘测,水下生物观测等方面具有极高的应用价值.为进一步提升仿章鱼臂软体机器人在特殊水下环境中控制效果,提出一种自适应鲁棒视觉伺服控制方法,实现其在干扰无标定环境中的高精度镇定控制.基于水底动力学模型,设计保证动力学稳定的控制器;针对柔性材料离线标定过程繁琐、成本高,提出材料参数自适应估计算法;针对水下特殊工作条件,设计自适应鲁棒视觉伺服控制器,实现折射效应的在线补偿,并通过自适应未知环境干扰上界,避免先验环境信息的求解.所提算法在软体机器人样机中验证其镇定控制性能,为仿生软体机器人的实际应用提供理论基础.

基于RBF最小参数学习法的正流量变量泵滑模自适应控制

为了提高正流量变量泵的性能,提出基于RBF最小参数学习法的正流量变量泵滑模自适应控制方法。分析正流量变量泵电液伺服系统的动力学特性,并进行系统辨识实验获得较为精确的系统数学函数模型;基于RBF最小参数学习法设计滑模控制器,在系统参数不确定性、摩擦力干扰和系统泄漏等非线性因素的情况下实现对目标流量的跟踪响应和自适应控制;最后利用MATLAB/Simulink对正流量变量泵的控制系统性能进行仿真实验,并和传统的PID控制器和模糊PID控制器进行比较。仿真实验结果验证了所设计控制方法的可行性和有效性。

盾构机电液伺服系统可变压力H_(∞)鲁棒控制设计

为了提高盾构机电液执行器能量消耗,结合比例溢流阀和比例方向控制阀优势,提出了一种电液伺服系统,并给出了运动控制方程。为实现节能效果,引入一种新的可变压力控制策略,选择鲁棒方法来达到最小的位置与能量消耗程度,利用Matlab软件仿真测试了执行器的运动控制性能与能量消耗情况。研究结果表明:经过改进处理后,执行器达到更低的位置跟踪误差,形成了0.01 mm之内的波动误差,相对误差不超过5%。对电液伺服系统改进后,在初始5 s时间内执行器消耗了较高功率,在50~130 W范围内保持波动状态,消耗的功率也较低。通过鲁棒H_(∞)方法对电液伺服系统运行过程进行控制时,执行器可以实现对运动位移的快速反应,获得理想的降能效果。该研究可为优化执行器的位置跟踪性能研究提供参考意义。