无轴传动凹版印刷机的相邻偏差耦合同步控制

针对无轴传动凹版印刷机的同步协调控制,考虑印刷基体张力恒定和套印准确的要求,基于相邻偏差耦合思想提出了一种能同时满足凹版印刷机无轴传动系统完全同步和比例同步特点的控制结构。针对无轴传动系统动力驱动部件非线性、强耦合的特点,设计了2阶自抗扰控制器以实现收放卷牵引单元与印刷色组单元高精度的跟踪控制和扰动补偿。构建了无轴传动凹版印刷机同步控制策略的仿真模型,仿真结果表明,提出的同步控制结构具有较高的同步控制精度和稳定性,设计的自抗扰控制器具有较好的速度跟踪性能和抗扰能力。     

气动伺服系统同步控制实验台的研究

气动同步控制是同步控制研究领域的关键问题。本文主要以气动同步控制试验台为研究对象，对该气动系统的基本特性和气动伺服系统的双缸位置同步控制问题进行研究，提出双层滑模变结构控制同步控制策略，进行双缸位置跟踪控制的实验研究。实验结果表明，提出的新型控制方法在双缸跟踪控制精度和抗干扰能力方面都十分有效。     

一种模糊补偿相邻耦合多轴同步控制结构研究

针对某轻工机械多轴转角位置同步控制精度问题,对多轴同步控制结构和控制策略进行了研究。在分析传统同步控制策略的基础上,针对研究对象转角位置同步误差要求,同时为了解决系统轴数较多时造成控制器在线计算量大的问题,改进了传统的交叉耦合同步结构,提出基于一种模糊补偿相邻耦合多轴同步控制结构。在相邻偏差补偿模块采用模糊PI(比例积分)控制算法,使得系统在负载扰动的情况下仍能保持良好的同步稳定性。仿真和实验对比结果表明,该同步策略控制精度较高、收敛速度快、满足稳定性要求,很好地实现了研究对象的同步控制要求。     

基于广义预测相邻耦合理论的多点顶推系统同步控制策略

针对多点顶推系统的同步控制问题,提出了一种广义预测相邻耦合同步控制策略。根据多变量广义预测理论,建立了多缸电液伺服系统的CARIMA模型。结合相邻耦合控制理论,构造了同步误差观测器,预测了同步误差。对广义预测控制算法进行了改进,在性能指标中嵌入跟踪误差与同步误差及其差分量,确保同步误差与跟踪误差在全局范围内并渐进收敛于零。实验表明该策略较之主从式PID控制策略,具有更好的跟踪性能和同步性能。     

自适应同步控制策略在3-PRR平面并联机构中的应用

本文以三自由度P—R—R型平面并联机构为研究对象,建立系统的动力学模型,结合同步控制和自适应控制两种控制方法的优缺点,提出了一种新颖的控制方法,称为自适应同步控制,用来提高并联机构不确定参数的跟踪精度。通过用自适应同步控制策略对被控对象进行控制仿真,其结果表明,自适应同步控制方法的跟踪效果好,精度高,系统误差小,可以满足并联机构控制的要求,能够解决机构的轨迹跟踪问题,证实了自适应同步控制策略的正确性和有效性。     

双电动缸滑模力分配同步起竖控制

针对含有未知系统动态、外部时变干扰及内力纷争的双电动缸同步起竖系统，提出了一种不依赖于函数逼近器且能保证瞬态和稳态跟踪性能的同步控制策略。设计基于未知系统动态估计的双曲滑模控制器保证起竖轨迹跟踪性能，使用未知系统动态估计器估计补偿系统未知参数和外部时变干扰，该控制器结构简单只需调节一个参数且具有良好的动态适应性能，基于双曲函数设计了一种新的滑模趋近律，有效克服了传统滑模的易抖振等问题；针对双电动缸同步起竖过程中存在的双缸耦合现象，设计推力分配同步控制算法，避免系统产生大的耦合内力，同时保证双缸运动的同步性。通过Lyapunov稳定性理论证明闭环系统的稳定性，仿真结果证明了提出控制策略的有效性。     

基于RBF神经网络的闭链下肢康复机器人自适应补偿控制

在下肢康复机器人的康复训练过程中,模型参数、环境干扰等不确定性因素会影响机器人轨迹跟踪的精度。针对这一问题,提出了一种基于径向基函数（Radial Basis Function,RBF）神经网络的自适应补偿控制,该控制方法能够提高机械系统轨迹跟踪的精确性。首先,设计一款具有4种工作模式、运动稳定的闭链卧式下肢康复机器人结构;然后,利用拉格朗日方法求解动力学名义模型,将康复装置的模型参数以及外界干扰等不确定性因素分离出来,并设计基于RBF神经网络的自适应补偿算法对其进行逼近控制;最后,通过Matlab/Simulink环境对其进行仿真验证,证明了该控制策略的有效性。结果显示,在人体步态曲线轨迹跟踪中,提出的基于RBF神经网络的自适应补偿算法相比传统的模糊比例-积分-微分（Proportional Integral Derivative,PID）控制的方法响应速度快、跟踪效果好,且髋关节和膝关节轨迹跟踪的角度误差峰值分别为0.08°和0.13°,远小于患者下肢在康复运动中的转动角度。设计了单腿样机试验,试验结果表明,采用的RBF补偿自适应控制器能够实现高精度的跟踪结果,也能够满足患者在康复...     

机载光电平台的复合补偿控制方法

为实现机载光电平台的实时高精度稳定跟踪控制,提出了一种基于改进干扰观测器和模糊逼近的复合自适应补偿控制方法.首先,根据系统的机械结构特点分析了各框架间的运动学耦合关系;考虑到载体扰动的影响,提出了一种基于速度信号的改进干扰观测器结构,并分析了它的工作原理和鲁棒稳定性.然后,针对机械系统中普遍存在的摩擦等干扰现象,设计了基于模糊逼近的复合补偿控制策略以保证系统的跟踪性能,最后,利用Lyapunov稳定性理论证明了系统的全局稳定性和跟踪误差的渐进收敛.实验结果显示,该控制方法具有较高的稳定精度,其跟踪误差可达μrad数量级,表明该方法可以有效地抑制载体扰动的影响并且具有良好的跟踪性能,是可行有效的.     

输入受限无人帆船自适应航向跟踪控制

针对带有输入受限且存在未知控制系数约束情形下,考虑了具有未知模型和风、浪等外界干扰的无人船航向跟踪控制问题,提出一种受限控制输入约束下的跟踪控制方法。该方法运用RBF神经网络对未知模型进行在线逼近,利用Nussbaum自适应增益技术解决未知控制系数问题。根据滑模控制理论,设计具有指数趋近律的鲁棒控制项,保证所得误差闭环系统快速响应且最终趋向0。为弱化传统滑模控制产生的抖振问题,将符号函数替换成饱和函数使控制输入变得平滑。引入一种误差辅助系统,构建了帮助误差闭环系统输入退出饱和机制。通过李雅普诺夫稳定性理论,给出了跟踪控制方法的稳定性数学分析过程,证明误差闭环跟踪控制系统的所有信号最终一致有界性。最后通过仿真结果验证了所得理论的有效性。     

基于反演设计的机械臂非奇异终端神经滑模控制

针对具有建模误差和不确定干扰的多关节机械臂的轨迹跟踪问题,设计反演非奇异终端神经滑模控制。该方案是采用能有限时间收敛的非奇异终端滑模面,根据滑模控制原理和反演方法设计反演滑模控制器;对于反演滑模控制系统中由于建模误差和不确定干扰造成的不确定因素的上界,设计径向基(Radial basis function, RBF)神经网络自适应律,在线估计不确定因素的上界;利用李亚普诺夫定理证明了系统的稳定性。仿真结果表明,该方法具有良好的轨迹跟踪性能,提高对于建模误差和不确定干扰等因素的鲁棒性,削弱了抖动。     

机械手鲁棒自适应PD控制

针对工业机械手的轨迹跟踪问题,设计了一种鲁棒自适应PD控制策略,避免了初始输出力矩过大的弊端.考虑将控制器分为非线性补偿控制和PD反馈控制两部分,机械手的不确定动力学部分由回归矩阵构成的自适应控制器进行补偿,实现了对机械手的运动控制.通过计算机仿真结果验证了所提出控制策略的有效性,能够很好地跟踪期望轨迹.     

Adaptive control of 5 DOF upper-limb exoskeleton robot with improved safety

This paper studies an adaptive control strategy for a class of 5 DOF upper-limb exoskeleton robot with a special safety consideration. The safety requirement plays a critical role in the clinical treatment when assisting patients with shoulder, elbow and wrist joint movements. With the objective of assuring the tracking performance of the pre-specified operations, the proposed adaptive controller is firstly designed to be robust to the model uncertainties. To further improve the safety and fault-tolerance in the presence of unknown large parameter variances or even actuator faults, the adaptive controller is on-line updated according to the information provided by an adaptive observer without additional sensors. An output tracking performance is well achieved with a tunable error bound. The experimental example also verifies the effectiveness of the proposed control scheme.     

On position/force tracking control problem of cooperative robot manipulators using adaptive fuzzy backstepping approach

In this paper, the position and force tracking control problem of cooperative robot manipulator system handling a common rigid object with unknown dynamical models and unknown external disturbances is investigated. The universal approximation properties of fuzzy logic systems are employed to estimate the unknown system dynamics. On the other hand, by defining new state variables based on the integral and differential of position and orientation errors of the grasped object, the error system of coordinated robot manipulators is constructed. Subsequently by defining the appropriate change of coordinates and using the backstepping design strategy, an adaptive fuzzy backstepping position tracking control scheme is proposed for multi-robot manipulator systems. By utilizing the properties of internal forces, extra terms are also added to the control signals to consider the force tracking problem. Moreover, it is shown that the proposed adaptive fuzzy backstepping position/force control approach ensures all the signals of the closed loop system uniformly ultimately bounded and tracking errors of both positions and forces can converge to small desired values by proper selection of the design parameters. Finally, the theoretic achievements are tested on the two three-link planar robot manipulators cooperatively handling a common object to illustrate the effectiveness of the proposed approach.     

凿岩机器人轨迹跟踪自适应预测控制

将一种输入输出增量式线性时变模型作为对象的实时预测模型 ,采用加权限定记忆回归法来估计模型参数 ,进而提出一种自适应预测控制策略 ,并给出了单步预测最优控制律。简要介绍了凿岩机器人双三角钻臂的结构和运动特性 ,随后将本文提出的自适应预测控制策略用于双三角钻臂轨迹跟踪控制 ,仿真结果表明了该控制策略的可行性。     

液压机器人作动器建模及关节转角跟踪控制

针对液压四足机器人作动器伺服精度较差问题,分别推导电液伺服作动器在摆动相、刚性支撑相和弹性支撑相的等效模型,分析各作动器模型特点,提出比例内环自适应幅相控制外环的复合控制策略,应用比例控制器保证位置内环的稳定性,采用自适应幅相控制器进行幅值和相位补偿。通过机器人单腿测试平台进行控制策略验证,实验结果表明:所提控制策略可使系统幅值衰减小于2%,相位滞后小于4°,验证了此方法的有效性。     

A switching formation strategy for obstacle avoidance of a multi-robot system based on robot priority model

This paper describes a switching formation strategy for multi-robots with velocity constraints to avoid and cross obstacles. In the strategy, a leader robot plans a safe path using the geometric obstacle avoidance control method (GOACM). By calculating new desired distances and bearing angles with the leader robot, the follower robots switch into a safe formation. With considering collision avoidance, a novel robot priority model, based on the desired distance and bearing angle between the leader and follower robots, is designed during the obstacle avoidance process. The adaptive tracking control algorithm guarantees that the trajectory and velocity tracking errors converge to zero. To demonstrate the validity of the proposed methods, simulation and experiment results present that multi-robots effectively form and switch formation avoiding obstacles without collisions.     

Direct adaptive robust tracking control for 6 DOF industrial robot with enhanced accuracy

A direct adaptive robust tracking control is proposed for trajectory tracking of 6 DOF industrial robot in the presence of parametric uncertainties, external disturbances and uncertain nonlinearities. The controller is designed based on the dynamic characteristics in the working space of the end-effector of the 6 DOF robot. The controller includes robust control term and model compensation term that is developed directly based on the input reference or desired motion trajectory. A projection-type parametric adaptation law is also designed to compensate for parametric estimation errors for the adaptive robust control. The feasibility and effectiveness of the proposed direct adaptive robust control law and the associated projection-type parametric adaptation law have been comparatively evaluated based on two 6 DOF industrial robots. The test results demonstrate that the proposed control can be employed to better maintain the desired trajectory tracking even in the presence of large parametric uncertainties and external disturbances as compared with PD controller and nonlinear controller. The parametric estimates also eventually converge to the real values along with the convergence of tracking errors, which further validate the effectiveness of the proposed parametric adaption law.     

Human-tracking strategies for a six-legged rescue robot based on distance and view

Human tracking is an important issue for intelligent robotic control and can be used in many scenarios, such as robotic services and human-robot cooperation. Most of current human-tracking methods are targeted for mobile/tracked robots, but few of them can be used for legged robots. Two novel human-tracking strategies, view priority strategy and distance priority strategy, are proposed specially for legged robots, which enable them to track humans in various complex terrains. View priority strategy focuses on keeping humans in its view angle arrange with priority, while its counterpart, distance priority strategy, focuses on keeping human at a reasonable distance with priority. To evaluate these strategies, two indexes(average and minimum tracking capability) are defined. With the help of these indexes, the view priority strategy shows advantages compared with distance priority strategy. The optimization is done in terms of these indexes, which let the robot has maximum tracking capability. The simulation results show that the robot can track humans with different curves like square, circular, sine and screw paths. Two novel control strategies are proposed which specially concerning legged robot characteristics to solve human tracking problems more efficiently in rescue circumstances.     

蛇形机器人跟踪误差预测的自适应轨迹跟踪控制器

为了满足蛇形机器人轨迹跟踪运动的精度需要,消除外界干扰对机器人跟踪误差的影响,提出了一种蛇形机器人跟踪 误差预测的自适应轨迹跟踪控制器。 所提出的控制器实现了机器人干扰变量、摩擦系数和控制参数的预测,并用预测值和虚拟 控制函数来补偿系统的控制输入,抵消了蛇形机器人在轨迹跟踪过程中的侧滑角,避免了干扰变量对机器人带来的负面影响, 提高了轨迹跟踪的误差稳定性与控制精度。 在建立蛇形机器人模型后,利用积分形式的侧滑角补偿项改进了视线法,并设计了 蛇形机器人的自适应轨迹跟踪控制器。 使机器人的位置误差在 10 s 内实现收敛,角度误差小于 0. 03 rad,预测值误差在 5 s 内 收敛。 通过仿真实验,验证了所提出的控制器的有效性和优越性。     

事件触发的自适应移动机器人轨迹跟踪控制

针对纵向滑转对移动机器人轨迹跟踪控制的影响,提出了一种基于事件触发的自适应轨迹跟踪控制方法。引入自适应估计策略,通过两个滑转参数自适应估计驱动轮的纵向滑转情况,克服纵向滑转带来的运动扰动。同时结合事件触发思想,设计触发函数,降低通信频次,节约计算资源。最后,利用Lyapunov稳定性理论对系统的稳定性进行证明。仿真及实验结果表明,在纵向滑转使得位置误差最大值的均方根提升56.85%的情况下,控制系统仍能在短时间内迅速收敛,提高了运动系统的稳定性。