精密转台S曲线轨迹规划及高精度控制

为提升精密转台的轨迹运动精度,本文从轨迹规划和运动控制两个方面对传统控制算法进行了改进。轨迹规划方面,推导了S曲线轨迹规划方程,并结合转台动力学约束条件给出了轨迹规划参数的取值方法,从而为运动控制算法提供了满足动力学要求的轨迹指令;运动控制方面,在传统双闭环反馈控制基础上增加了DOB扰动补偿和前馈补偿,以此改善转台的伺服性能,提升转台的运动精度。在详细说明了轨迹规划算法和运动控制算法的设计过程后,对两部分算法进行综合,给出了具体实现步骤,并以谐波转台和RV转台为实验对象进行了多组算法性能测试。实验结果表明:相比于传统控制方法,采用本文提出的方法能够使转台动态精度提升99.6%,稳态精度提升99.75%,从而证实了该算法对运动精度提升的有效性。     

Trajectory planning and tracking control of a ground mobile robot:A reconstruction approach towards space vehicle

With the development of the similarity calculation method, the orbital motion of space vehicle can be translated into a sequence of waypoints that reflect position and velocity on the ground. In this paper, a motion control system is proposed to make the mobile robot pass through the desired waypoints for reconstructing the orbital motion. First, the parameterized trajectory optimization method is applied to generate a curvature-continuous trajectory from the waypoints, the position and velocity demands are presented as the equality constraints. Virtual positions are introduced to reduce the oscillation, and the total execution time of the whole trajectory is selected as the optimization parameter to reduce the computational burden. Then, an equivalence transformation is provided to translate the error system into an affine form, which is beneficial for the feedback controller design. Based on this, a nonlinear trajectory tracking controller is proposed, which includes a feedforward controller and an error feedback controller, and its exponential stability is proved using Persistency of Excitation Lemma. In addition, a shunting neural dynamics model is employed to avoid sharp velocity jumps. Finally, the performed experiments verify the effectiveness of the proposed method.     

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。     

Motion error compensation of multi-legged walking robots

Existing errors in the structure and kinematic parameters of multi-legged walking robots,the motion trajectory of robot will diverge from the ideal sports requirements in movement.Since the existing error compensation is usually used for control compensation of manipulator arm,the error compensation of multi-legged robots has seldom been explored.In order to reduce the kinematic error of robots,a motion error compensation method based on the feedforward for multi-legged mobile robots is proposed to improve motion precision of a mobile robot.The locus error of a robot body is measured,when robot moves along a given track.Error of driven joint variables is obtained by error calculation model in terms of the locus error of robot body.Error value is used to compensate driven joint variables and modify control model of robot,which can drive the robots following control model modified.The model of the relation between robot’s locus errors and kinematic variables errors is set up to achieve the kinematic error compensation.On the basis of the inverse kinematics of a multi-legged walking robot,the relation between error of the motion trajectory and driven joint variables of robots is discussed.Moreover,the equation set is obtained,which expresses relation among error of driven joint variables,structure parameters and error of robot’s locus.Take MiniQuad as an example,when the robot MiniQuad moves following beeline tread,motion error compensation is studied.The actual locus errors of the robot body are measured before and after compensation in the test.According to the test,variations of the actual coordinate value of the robot centroid in x-direction and z-direction are reduced more than one time.The kinematic errors of robot body are reduced effectively by the use of the motion error compensation method based on the feedforward.     

基于LuGre模型的自适应摩擦补偿

为提高开放式伺服系统的动态性能,使其具有良好的适应能力,提出一种基于LuGre模型的自适应摩擦补偿方法.建立开放式伺服系统的动力学模型,并通过LuGre模型来描述系统的摩擦特性.考虑到摩擦模型的参数会随系统变化而发生改变,采用Backstepping方法设计自适应摩擦补偿控制器,并采用Lyapunov定理证明系统的全局渐进稳定性.通过可编程多轴控制器(Programmable multi-axis controller,PMAC)编写伺服算法实现该自适应摩擦补偿方案,并通过试验验证该方案的有效性.试验结果表明:与传统的速度加速前馈补偿相比,该自适应摩擦补偿方案在正弦运动作为输入信号时,其跟踪误差由±40 μn降低到±7 μm.采用该补偿方案能有效地抑制摩擦干扰对伺服系统的不利影响,为提高伺服系统的动态跟踪性能奠定基础.     

考虑外部扰动的四轮移动机器人运动轨迹控制优化方法

控制机器人的运动轨迹，有助于提高四轮移动机器人工作的整体性能，提出考虑外部扰动的四轮移动机器人运动轨迹控制优化方法，利用人工势场法根据机器人运动特点规划其运动轨迹。考虑外部扰动和不确定性因素，结合低通滤波器和滑膜控制器设计运动轨迹控制器，实现四轮移动机器人运动轨迹的优化控制。实验结果表明，所提方法的轨迹控制效果好，距离误差小，稳定性高。     

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.     

考虑控制电信号中间量的机床运动控制误差数据驱动建模方法

现有数据驱动的机床运动控制误差建模方法通常使用端到端的模型,即通过机器学习算法直接构建参考轨迹信息(速度、加速度等)与伺服误差之间的模型,以降低建模复杂度。然而,该方法忽视了控制电信号对运动控制系统非线性扰动的反映,而导致建立的模型精度受限。为解决此问题,提出了一种使用控制电信号作为中间量的数据驱动运动控制误差建模方法。该方法采集参考轨迹信息(速度、加速度、急动度等)、控制电信号、跟踪误差以及构造的换向特征,构建并训练基于参考轨迹信息的控制电信号预测网络,以及基于电信号和参考轨迹信息的运动控制误差预测网络,利用控制电信号这一中间量有效反应系统所受非线性扰动的特点,实现了高精度的运动控制误差数据驱动建模。在实际验证测试时,将参考轨迹信息输入电信号预测网络,而后将得到的预测控制电信号和参考轨迹信息输入跟踪误差预测网络,即可实现运动控制误差的预测。通过实验对所提出的建模方法进行了验证,所提出方法相对于传统的端到端建模方法,运动控制误差的预测精度在X轴和Y轴分别提升16.33%和20.42%,误差补偿后运动控制轮廓精度相较于未补偿提升85.59%,验证了所提出方法的可行性。     

参数不确定双臂空间机器人姿态、关节协调运动的变结构鲁棒控制方法

讨论了载体位置不受控制情况下,具有参数不确定性的漂浮基双臂空间机器人姿态、关节协调运动的控制问题。结合系统动量守恒关系进行的系统运动学、动力学分析表明,可以得到一组与适当选择的组合惯性参数呈线性函数关系的系统动力学方程。以此为基础,针对双臂空间机器人末端爪手所持载荷参数不确定,但误差范围可确定的情况,设计了漂浮基双臂空间机器人姿态、关节协调运动的变结构鲁棒控制方案。该控制方案的优点在于:不需要反馈、测量漂浮基的位置、移动速度及移动加速度,且与自适应控制方案相比,化积分运算为简单四则运算,计算量大为减少,有利于克服机载计算机计算能力有限的问题。一个平面双臂空间机器人的系统数值仿真,证实了方法的有效性。     

基于模糊神经网络的不确定机器人实时轨迹跟踪控制的研究

针对机器人建模的不精确性以及扰动的存在给机器人控制增加难度的问题,提出了一种基于模糊神经网络的不确定机器人实时轨迹跟踪控制方法。该控制方法的控制器由模糊神经网络(FNN)控制器和CMAC控制器组成,FNN控制器代替传统的计算力矩法,CMAC控制器在线补偿控制误差,有效补偿机器人存在的各种不确定性。对二自由度机器人的仿真结果表明了所提出的控制方法的可行性。     

Control and dynamic releasing method of a piezoelectric actuated microgripper

This paper proposes the control and dynamic releasing method of a symmetric microgripper with integrated position sensing. The microgripper adopted in this micromanipulation system is constructed by two L-shaped leverage mechanisms and the fingers of the microgripper is machined much thinner than the gripper body. A combined feedforward/feedback position controller is established to improve the motion accuracy of the microgripper in high frequency. The feedforward controller is established based on rate-dependent inverse Prandtl-Ishlinskii (P–I) hysteresis model. The inertial force generated in dynamic based releasing process is analyzed through MATLAB simulation. Open-loop experimental tests have been performed, and the results indicate the first natural frequency of the microgripper is 730 Hz. Then experiments in high frequency based on the developed combined controller are carried out and the results show the tracking error of a superimposed sinusoidal trajectory with the frequency of 100 Hz, 120 Hz and 130 Hz is 6.4%. Finally, the tiny objects releasing experiments are conducted where the combined controller is used to control the motion amplitude and frequency to achieve inertial force controllable to improve operation accuracy. And the results show that the dynamic releasing strategy is effective.     

Controller Parameter Tuning of Delta Robot Based on Servo Identification

High-speed pick-and-place parallel robot is a system where the inertia imposed on the motor shafts is real-time changing with the system configurations.High quality of computer control with proper controller parameters is conducive to overcoming this problem and has a significant effect on reducing the robot’s tracking error.By taking Delta robot as an example,a method for parameter tuning of the fixed gain motion controller is presented.Having identifying the parameters of the servo system in the frequency domain by the sinusoidal excitation,the PD+feedforward control strategy is proposed to adapt to the varying inertia loads,allowing the controller parameters to be tuned by minimizing the mean square tracking error along a typical trajectory.A set of optimum parameters is obtained through computer simulations and the effectiveness of the proposed approach is validated by experiments on a real prototype machine.Let the traveling plate undergoes a specific trajectory and the results show that the tracking error can be reduced by at least 50%in comparison with the conventional auto-tuning and Z-N methods.The proposed approach is a whole workspace optimization and can be applied to the parameter tuning of fixed gain motion controllers.     

A study on tracking error based on mechatronics model of a 5-DOF hybrid spray-painting robot

Industrial robots suffer from difficulties in predicting and guaranteeing tracking performance due to the complex dynamic behavior and inaccurate mechatronics model. This study investigates the tracking error and motion accuracy improvement based on a mechatronics model of a 5-degree of freedom hybrid spray-painting robot. The dynamic model of the robot is derived by using Lagrange equation, and an identification method is presented to identify the torque coefficient and joint friction synchronously. An accurate mechatronics model is established after the theoretical dynamic modeling and friction identification. The tracking error generation mechanism of the robot control system is studied, and its analytical equation is derived on the basis of a transfer function. A multichannel feedforward controller is synthesized to reduce the tracking error from different sources. The effectiveness of the proposed method in improving tracking accuracy is verified by physical experiments.

     

基于标定和关节空间插值的工业机器人轨迹误差补偿

轨迹精度是工业机器人重要的动态性能,目前工业机器人的轨迹精度远低于定位精度,提出一种基于机器人运动学标定和关节空间插值误差补偿的方法来提高机器人轨迹精度。基于MD-H方法建立机器人的运动学模型,在此基础上运用机器人微分运动学理论建立末端位置误差模型和轨迹误差模型。为克服最小二乘法等传统方法在数据噪声较大且不符合高斯分布时收敛慢甚至发散的问题,提出一种基于扩展卡尔曼滤波算法的机器人运动学参数辨识方法,实现运动学参数辨识的快速收敛。经过分析发现机器人误差在关节空间具有连续性的特点,为此提出一种关节空间插值误差补偿方法,建立网格形式的误差补偿数据库,并利用关节空间距离权重函数和已知的网格顶点误差计算各控制点的关节转角误差。通过试验对所提出的参数辨识和关节空间误差补偿方法进行了验证,试验结果表明：经过运动学参数辨识和补偿后机器人的绝对定位精度由1.039 mm提高到0.226 mm,轨迹精度由2.532 mm提高到1.873 mm,应用关节空间插值误差补偿后机器人的轨迹精度进一步提高到1.464 mm。     

基于RBFMCN网络的电液速度伺服系统的动态补偿控制算法

基于一种改进的径向基函数网络,提出一种电液伺服系统自学习动态补偿控制算法。控制器包括1个神经网络动态补偿控制器和1个神经网络自学习控制器。算法用于承受交变负载变化的阀控缸电液速度伺服系统的动态补偿控制,取得了令人满意的仿真及实验结果。     

2R耦合驱动关节动力学建模与参数辨识

围绕护理机器人的人机安全接触和轻量大负载需求,提出了一种2R耦合驱动关节构型,并解决了耦合驱动动力学建模问题,为高性能运动控制器搭建提供基础。该关节设计紧凑、负载能力强,两个伺服电机经过三级减速后,通过差动结构实现两自由度耦合输出,且表面光滑适宜与人接触。通过运动学分析了耦合驱动的原理,利用拉格朗日法建立了耦合驱动动力学模型。为解决速度零点摩擦力不连续,造成基于模型的控制器运动性能变差的问题,引入了连续可微摩擦模型,利用连续可微特性采用灰色模型提高了辨识精度。研制了机器人关节样机,进行了关节解耦、摩擦数据采集、参数辨识及轨迹跟踪等试验,结果表明所设计的耦合驱动关节可以完成周转、俯仰两个转动自由度的单独及耦合运动,并且输出扭矩与重量的比值达到了143.6 N·m/kg,可以满足轻量大负载护理需求,同时基于所建立动力学模型的运动控制可以显著提高轨迹跟踪的准确性。     

An improved force-based impedance control method for the HDU of legged robots

Hydraulic drive mode enables legged robots to have excellent characteristics, such as greater power-to-weight ratios, higher load capacities, and faster response speeds than other robots. Nowadays, highly integrated valve-controlled cylinder, called hydraulic drive unit (HDU), is employed to drive the joints of these robots. However, various robot control issues exist. For example, during the walking process of legged robots, different obstacles are encountered, making it difficult to control such robots because the load characteristics of the ends of their feet change with the environment. Furthermore, although the adoption of HDU has resulted in high-performance robot control, the hydraulic systems of these robots still have problems, such as strong nonlinearity, and time-varying parameters. Consequently, robot control is very difficult and complex. This paper proposes an improved second-order dynamic compliance control system, impedance control, for HDU. The control system is designed to rectify the issues affecting the impedance control accuracy of the dynamic compliance serial–parallel composition between the HDU force control inner loop and the impedance control outer loop. Specifically, it consists of a compliance-enhanced controller and a feedforward compensation controller for the force control inner loop. Furthermore, the dynamic compliance composition of the inner and outer HDU control loops is rearranged. The results of experiments conducted indicate that the proposed method significantly improves the control accuracy compared to that of traditional force-based impedance control.     

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.     

液压驱动单元位置控制系统前馈补偿控制研究

液压驱动型足式机器人在运动过程中各关节液压驱动单元（Hydraulic drive unit,HDU）多采用基于液压控制内环的外环阻抗控制方法,其中液压控制内环可分为位置闭环控制和力闭环控制。当液压控制内环采用位置闭环控制时,其位置控制性能直接决定了外环阻抗控制性能,所以,一种针对HDU的高精度的位置控制方法具有重要研究意义。针对以上研究意义,首先对HDU位置控制系统6阶数学模型进行简化,求出位置控制系统中各部分传递函数。其次,推导位置控制输入前馈补偿控制器,该控制器中含有液压系统固有非线性和负载特性。最后,在HDU性能测试试验平台上,在多种典型输入信号以及对角小跑输入信号下,对系统的位置控制性能进行试验研究并给出定量分析。试验结果表明,在不同输入信号下,加入所提出的输入前馈补偿控制器可以大幅提高系统位置控制性能,并且该控制器具有良好的多工况适应性。以上研究成果可结合相应的针对位置控制系统的抗干扰控制策略,一起为基于位置的阻抗控制液压内环控制提供控制策略重要参考和试验基础。     

Control system design of a linear motor feed drive system using virtual friction

This paper proposes a friction compensator and a design method for control systems to improve the response characteristics of linear motor feed drive systems. The proposed friction compensator cancels the real nonlinear friction of feed drive systems by using the nonlinear friction model proposed in this study and introduces virtual linear friction to facilitate the control system design. The proposed design method enables the determination of servo gains and friction compensator parameters that lead to desirable tracking performance and disturbance rejection without many trial-and-error tuning processes. In addition, the proposed method facilitates the design of the velocity feedforward compensator by using the inverse transfer function of the velocity control loop to correct the position tracking errors for various position commands. The effectiveness of the proposed method with the friction compensator and the velocity feedforward compensator was verified in simulations and experiments using a one-axis feed drive system consisting of a rod-type linear motor and linear roller guides. The results confirmed that the proposed method enables desirable overshoot-free responses and corrects motion trajectory errors due to nonlinear friction characteristics, and the proposed velocity feedforward compensator can correct tracking errors in both constant velocity motion and circular motion.