气动肌肉驱动关节轨迹跟踪的自适应鲁棒控制

设计了一种简单、经济的单根肌肉关节驱动上肢外骨骼助力机器人.为解决单根肌肉关节轨迹跟踪控制精度差、抗干扰能力差及颤振严重等问题,基于反步法设计单根肌肉关节伺服系统的自适应鲁棒控制器.该控制器呈两层级联结构,每层均包含一个鲁棒反馈、参数自适应及快速动态补偿项,基于递归最小二乘法和梯度法分别设计参数自适应及快速动态补偿项....     

基于摩擦补偿的柔性关节机器人分级滑模控制

针对柔性关节机器人中存在的非线性摩擦问题,提出一种基于摩擦补偿的柔性关节机器人分级滑模控制方法。首先,通过线性化参数的方法对柔性关节机器人受到的摩擦进行建模,并对模型中未知参数设计自适应律以实现摩擦的估计;然后,针对摩擦模型的误差,进一步设计观测器进行估计,结合摩擦的自适应和模型误差估计实现对摩擦的补偿;最后,利用电机侧和关节侧的位置误差和速度误差设计一级滑模面,再根据一级滑模面设计二级滑模面,从而得到分级滑模控制器,进一步实现柔性关节机器人的位置轨迹跟踪控制。通过Lyapunov函数证明了机器人关节轨迹跟踪误差的收敛性。仿真结果表明：该控制方法结合参数自适应和模型误差观测器可以有效地对摩擦进行补偿,在有限时间内实现柔性关节机器人的位置轨迹对期望位置轨迹的跟踪。     

基于H∞理论的滚珠丝杠进给系统滑模控制

针对滚珠丝杠进给系统的动态特性,建立参数不确定的数学模型. 为了消除参数不确定的影响,设计满足H∞性能的积分滑模控制器. 针对存在的未知干扰,设计指数干扰观测器进行补偿. 分析结果表明,本研究的控制方法具有L₂增益性能. 利用该方法在滚珠丝杠实验台上进行轨迹跟踪实验. 实验结果表明,当使用设计的控制器时,最大跟踪误差为16.85 μm;当使用设计的控制器加上指数干扰观测器时,最大跟踪误差为10.18 μm;在工作台增加25 kg质量块后,当使用设计的控制器加上干扰观测器时,最大跟踪误差为15.61 μm. 实验结果说明所设计的控制器具有较好的性能,并且干扰观测器能够提高控制精度. 与传统的比例-比例积分控制器的对比结果说明本研究的控制方法有较好的综合性能.     

Modeling and control of hydraulic excavator’s arm

In order to find a feasible way to control excavator’s arm and realize autonomous excavation, the dynamic model for the boom of excavator’s arm which was regarded as a planar manipulator with three degrees of freedom was constructed with Lagrange equation. The excavator was retrofitted with electrohydraulic proportional valves, associated sensors (three inclinometers) and a computer control system (the motion controller of EPEC). The full nonlinear mathematic model of electrohydraulic proportional system was achieved. A discontinuous projection based on an adaptive robust controller to approximate the nonlinear gain coefficient of the valve was presented to deal with the nonlinearity of the whole system, the error was dealt with by robust feedback and an adaptive robust controller was designed. The experiment results of the boom motion control show that, using the controller, good performance for tracking can be achieved, and the peak tracking error of boom angles is less than 4°. Foundation item: Project(2003AA430200) supported by the National Hi-Tech Research and Development Program(863) of China     

机器人系统鲁棒轨迹跟踪控制器设计

针对机器人系统的轨迹跟踪控制问题,考虑实际系统中存在的不确定性,基于动态系统终值有界性引理,采用连续状态反馈的方法,设计出一种鲁棒轨迹跟踪控制器。仿真结果表明,此法设计的控制器对机器人系统的参数不确定性具有较好的鲁棒性,可保证不确定性存在情况下跟踪误差的终值有界性。     

复合材料成形液压机自适应鲁棒运动控制

针对复合材料液压机电液系统中广泛存在的参数不确定性、不确定非线性和外干扰,设计基于非连续映射的非线性自适应鲁棒运动控制器. 自适应控制器对系统参数进行在线估计,所估计的参数虽不能完全收敛到真实值,但可以限定在上确界和下确界范围内,满足鲁棒控制不确定量上、下界的要求;参数自适应律渐进消除了参数不确定性引起的模型补偿误差,保证输出跟踪可以拥有规定的瞬态和稳态响应性能. 鲁棒控制律可以抑制未建模动态、参数估计误差和外干扰的影响. 利用Lyapunov稳定性理论证明了系统的稳定性. 仿真和实验结果表明,设计的控制器对所规划的运动轨迹具有精确的跟踪控制和强鲁棒的控制性能.     

AGV建模和自适应模糊滑模跟踪控制研究

介绍了自动导引小车AGV的跟踪控制技术的研究现状;建立了AGV跟踪误差系统运动学和动力学的混合模型;针对AGV的初始位存在误差或给定轨迹不连续时,传统PID轨迹跟踪控制器会使其初始速度产生一个较大跳变的问题,将滑模变结构控制技术与自适应模糊控制技术相结合,提出了一种基于模糊滑模的AGV自适应模糊路径跟随和轨迹跟踪控制器。仿真和实验结果表明,给出的自适应模糊滑模控制器不仅有较好的轨迹跟踪控制效果,而且具有较强的鲁棒性。     

基于PD方法的不确定机器人神经网络变结构控制

针对不确定机器人轨迹跟踪控制,提出基于PD方法自适应神经网络变结构控制律,利用RBF神经网络补偿系统参数不确定性,用滑模变结构控制器消除神经网络的逼近误差.仿真结果表明,该控制律能保证轨迹跟踪误差的快速收敛性及对参数不确定性和外部扰动的鲁棒性.     

Trajectory tracking control for underactuated unmanned surface vehicles with dynamic uncertainties

The trajectory tracking control problem for underactuated unmanned surface vehicles(USV) was addressed, and the control system took account of the uncertain influences induced by model perturbation, external disturbance, etc. By introducing the reference, trajectory was generated by a virtual USV, and the error equation of trajectory tracking for USV was obtained, which transformed the tracking problem of underactuated USV into the stabilization problem of the trajectory tracking error equation. A backstepping adaptive sliding mode controller was proposed based on backstepping technology and method of dynamic slide model control. By means of theoretical analysis, it is proved that the proposed controller ensures that the solutions of closed loop system have the ultimate boundedness property. Simulation results are presented to illustrate the effectiveness of the proposed controller.     

Synchronous tracking control of 6-DOF hydraulic parallel manipulator using cascade control method

The synchronous tracking control problem of a hydraulic parallel manipulator with six degrees of freedom (DOF) is complicated since the inclusion of hydraulic elements increases the order of the system. To solve this problem, cascade control method with an inner/outer-loop control structure is used, which masks the hydraulic dynamics with the inner-loop so that the designed controller takes into account of both the mechanical dynamics and the hydraulic dynamics of the manipulator. Furthermore, a cross-coupling control approach is introduced to the synchronous tracking control of the manipulator. The position synchronization error is developed by considering motion synchronization between each actuator joint and its adjacent ones based on the synchronous goal. Then, with the feedback of both position error and synchronization error, the tracking is proven to guarantee that both the position errors and synchronization errors asymptotically converge to zero. Moreover, the effectiveness of the proposed approach is verified by the experimental results performed with a 6-DOF hydraulic parallel manipulator.     

Adaptive fuzzy integral sliding mode pressure control for cutter feeding system of trench cutter

A nonlinear pressure controller was presented to track desired feeding pressure for the cutter feeding system (CFS) of trench cutter (TC) in the presence of unknown external disturbances. The feeding pressure control of CFS is subjected to unknown load characteristics of rock or soil; in addition, the geological condition is time-varying. Due to the complex load characteristics of rock or soil, the feeding velocity of TC is related to geological conditions. What is worse, its dynamic model is subjected to uncertainties and its function is unknown. To deal with the particular characteristics of CFS, a novel adaptive fuzzy integral sliding mode control (AFISMC) was designed for feeding pressure control of CFS, which combines the robust characteristics of an integral sliding mode controller and the adaptive adjusting characteristics of an adaptive fuzzy controller. The AFISMC feeding pressure controller is synthesized using the backstepping technique. The stability of the overall closed-loop system consisting of the adaptive fuzzy inference system, integral sliding mode controller and the cutter feeding system is proved using Lyapunov theory. Experiments are conducted on a TC test bench with the AFISMC under different operating conditions. The experimental results demonstrate that the proposed AFISMC feeding pressure controller for CFS gives a superior and robust pressure tracking performance with maximum pressure tracking error within ±0.3 MPa.

     

液压并联6-DOF平台轨迹跟踪的干扰力补偿

为了消除液压并联6-DOF平台因各支链缸时变的负载耦合,以及摩擦和其他外力的干扰作用而引起的平台动态轨迹抖动现象,根据系统动力学模型的关节空间表达式,对关节干扰力的起因和对其运动的作用进行分析,在关节位置闭环控制基础上,分别设计基于结构不变性原理的支链抗负载干扰补偿器和基于系统模型的自适应滑模干扰观测补偿器,根据系统关节负载的变化率将两种补偿器利用模糊原则组合成综合补偿器,对干扰进行力闭环补偿.AMESim与MATLAB的联合仿真分析结果表明,该控制器使平台在复合干扰力作用下,能够平稳运行,与普通的位置闭环PID算法相比,有效地提高了系统的整体动态跟踪性能.     

基于双观测器的机器人自适应摩擦补偿控制

针对机器人系统中存在关节摩擦的问题,提出一种基于终端滑模观测器和摩擦状态观测器的双观测器自适应摩擦补偿反演控制方案:为避免速度测量带来的噪声影响,设计终端滑模观测器对机器人的速度进行估计;考虑到摩擦力无法直接获取,采用连续LuGre摩擦模型,设计摩擦状态观测器和摩擦参数自适应律,得到摩擦的估计值;结合摩擦估计值设计反演控制器,使机器人在受到关节摩擦影响的情况下能有效跟踪期望位置轨迹。最后通过Lyapunov函数证明闭环系统的稳定性以及机器人轨迹跟踪误差的收敛性,并通过MATLAB仿真验证该控制方案的有效性。仿真结果表明,该控制方法能有效抑制关节摩擦对机器人轨迹跟踪的影响,提高了系统的位置跟踪精度。     

工业机器人可变增益自适应迭代学习控制研究

为确保执行重复运动的工业机器人位置、速度的跟踪精度,提出一种可变增益自适应迭代学习控制算法。首先在PD反馈部分增加指数可变增益来加快算法收敛速度,然后在参数自适应部分设计广义误差函数来进一步减小轨迹跟踪误差,增强系统稳定性。通过Lyapunov函数对可变增益自适应迭代学习控制算法的收敛性进行了理论证明,最后利用仿真验证了该控制算法能有效减小机器人轨迹跟踪误差,并加快算法的收敛速度。     

Anti-Dead-Zone Integral Sliding Control and Active Vibration Suppression of a Free-floating Space Robot with Elastic Base and Flexible Links

Under the conditions of joint torque output dead-zone and external disturbance, the trajectory tracking and vibration suppression for a free-floating space robot (FFSR) system with elastic base and flexible links were discussed. First, using the Lagrange equation of the second kind, the dynamic model of the system was derived. Second, utilizing singular perturbation theory, a slow subsystem describing the rigid motion and a fast subsystem corresponding to flexible vibration were obtained. For the slow subsystem, when the width of dead-zone is uncertain, a dead-zone pre-compensator was designed to eliminate the impact of joint torque output dead-zone, and an integral sliding mode neural network control was proposed. The integral sliding mode term can reduce the steady state error. For the fast subsystem, an optimal linear quadratic regulator(LQR) controller was adopted to damp out the vibration of the flexible links and elastic base simultaneously. Finally, computer simulations show the effectiveness of the compound control method.     

一类不确定性二阶振动系统的自适应滑模控制

针对一类典型的二阶振动系统,基于滑模控制理论研究了系统的控制问题。考虑系统存在不确定性的情况下,考虑不确定性上界已知和未知,分别设计了滑模控制器和自适应滑模控制器,并引入模糊控制消除滑模抖振的影响。最后通过仿真试验研究,验证了所设计控制方法的有效性。     

基于视觉的移动机器人轨迹跟踪

借助视觉反馈,研究了质心与几何中心不重合的非完整移动机器人轨迹跟踪控制问题。利用固定在天花板上的摄像机系统,作者提出了一种基于视觉伺服的运动学跟踪误差模型;基于这个模型,在质心与几何中心和视觉参数未知的情形下,作者设计了自适应轨迹跟踪控制器,并运用李雅普诺夫方法严格证明了闭环系统的稳定性。Matlab仿真证明了控制器的有效性。     

电—气比例/伺服控制系统的控制方法研究

本文在简要地回顾了电—气比例/伺服控制技术的发展历史后,研究了采用最小二次型性能指标设计并由实时优化系统进行实验优化的最优状态反馈控制系统。并针对这一系统所存在的问题,采用了鲁棒控制方法,提出对原不稳定系统的鲁棒控制器设计方法。此外,本文还深入地研究了自适应控制和鲁棒自适应控制方法。实验证明本文研究的控制方法均收到预期的效果。     

双足机器人鲁棒轨迹跟踪控制

根据机器人的动态特性和鲁棒控制理论,利用拉格朗日法建立了Robonova-1机器人的动力学模型。针对机器人系统的跟踪轨迹控制问题,考虑该系统实际存在的不确定性,基于机器人系统中存在的不确定性的上界设计了一个鲁棒控制器。仿真实验结果证明,该鲁棒控制方法对模型的不确定性或外部干扰对机器人系统产生的影响具有一定的抑制作用,对双足机器人的控制是有效的。     

基于线性矩阵不等式的智能车轨迹跟踪控制

针对传统的基于精确数学模型的智能车轨迹跟踪控制器跟踪精度低,鲁棒性弱,很难适应复杂多变的驾驶环境等问题,结合线性矩阵不等式(LMI)鲁棒控制具有易于求解、抗干扰能力强等优点,提出基于LMI的智能车轨迹跟踪控制方法. 将车辆侧向动力学状态空间模型进行坐标变换,得到基于跟踪误差的车辆侧向动力学状态空间模型,采用饱和线性轮胎得到车辆侧向动力学多胞型模型;设计LMI反馈控制器,在控制器中引入前馈控制量,以消除侧向位置稳态误差. Carsim和Matlab/Simulink的联合仿真表明,该控制器在保证车辆稳定性的基础上具有较高的跟踪精度,对车速和路面附着系数具有较强的鲁棒性. 与模型预测控制器(MPC)和预瞄驾驶员模型(PDM)控制器进行对比,结果表明,设计的该控制器轨迹跟踪精度更优.