【作者】 熊根良；

【导师】 刘宏；

【作者基本信息】 哈尔滨工业大学 ， 机械电子工程， 2010， 博士

【摘要】 目前,柔性关节轻型机械臂由于具有高的负载/自重比、质量轻、功耗低等特点,被广泛应用于各种移动机器人或者平台上,在空间探索、军事侦察、反恐排爆和家庭服务等领域占据越来越重要的地位。从轻型机械臂的应用领域和范围来看,其工作任务多样化且工作环境随工作任务而改变。要么工作于危险、未知的复杂环境下,要么与人亲密接触。因此从安全操作及可靠性来说,轻型机械臂除了需要高精度的位置控制外,还需要其对未知工作环境的柔顺性,即当机器人与未知环境相接触时,不至于对机器人本身和操作对象造成损伤;这就需要对轻型机械臂实施柔顺控制。而实现柔性关节机械臂的柔顺控制的有效方法有:力/位混合控制和阻抗控制。再者由于轻型机械臂关节采用谐波齿轮减速以及关节处存在的力矩传感器,都使其关节柔性增大;这不但给轻型机械臂的控制带来了很大的挑战,而且使其在运动的过程中不可避免的存在振动以及运动结束后存在残余振动的问题。为了得到高性能的轻型机械臂,就必须抑制其振动以及残余振动。因此,本文除了对柔性关节轻型机械臂的位置控制进行研究外,还将对柔性关节轻型机械臂笛卡尔阻抗控制以及振动与残余振动抑制进行深入研究。本文研制了柔性关节轻型机械臂的硬件系统,包括机械系统、传感器系统以及电气系统,并对整个系统的电气布局进行了简要的介绍。即利用模块化设计思想设计了4自由柔性关节轻型机械臂,模块化关节具有丰富的传感器系统。同时建立了基于Xilinx FPGA的底层控制器、基于PCI的上层控制器以及实现上下层之间通讯的PP-LVDS高速串行总线,通讯周期为200us。底层控制器实现的功能包括:传感器数据采集、数据融合、电机的方波驱动以及与上层的通讯;上层控制器实现的功能有:运动学、动力学、轨迹规划以及与底层的通讯。基于反步法实现单连杆柔性关节轻型机械臂的位置控制,但由于其对系统模型参数变化敏感。因此,采用基于神经网络的自适应反步法控制器。既克服了传统反步法对模型参数敏感的问题,又消除了对柔性关节轻型机械臂精确动力学模型的需要,并不受关节柔性大小的限制,控制过程中无需连杆加速度及加加速度信息。仿真和实验结果证明该方法的有效性,同时,利用该方法控制轻型机械臂,测试其末端位置重复定位精度和姿态重复定位精度的均达到设计指标。采用反步法笛卡尔阻抗控制实现轻型机械臂的柔顺控制,在设计笛卡尔阻抗控制器的过程中,传统的反步法存在“项数膨胀”问题。为了解决此问题,提出了基于动态面控制-反步法阻抗控制器;该方法在每一步设计过程中引入一阶积分滤波器来估计虚拟控制输入的导数,从而既消除了传统反步法中存在的“项数膨胀”问题,又对可能包含传感器噪声的输入信号进行了滤波,提高系统的动态性能,最后给出了该控制器的稳定性证明。利用此方法实现了柔性关节机械臂在受限环境下的柔顺行为,从而证明该方法的有效性。由于谐波齿轮减速以及关节力矩传感器存在,使得轻型机械臂由关节的柔性引起的振动以及残余振动进行抑制控制。针对运动过程中由于干扰或自身柔性引起的振动,设计了基于Luenberger函数的关节状态观测器,利用电机位置传感器和关节力矩传感器,实现对关节位置和关节速度的观测。从而实现了柔性关节的全状态反馈控制,抑制了柔性关节机械臂在运动过程中由于外力扰动或自身柔性引起的振动。而对于运动停止后存在的残余振动,引入时变输入整形技术对机械臂进行控制。当模型不准确时采用离线方法,获得主振模态随构型变化函数,基于这个函数实时修改输入整形器参数,达到抑制残余振动的目的;当模型准确时通过动力学模型求解特征值获得振动模态随构型变化函数,基于此函数实现自适应输入整形控制,从而实现机械臂的残余振动抑制。上述两种方法针对的是机械臂空载情况;对于带载情况下,采用基于模型的自适应输入整形方法。本文位置控制和振动以及残余振动抑制方法的实现是在第一代四自由度柔性关节轻型机械臂上进行的;而笛卡尔阻抗控制是在第二代五自由度柔性关节轻型机械臂上实现的。更多还原

【Abstract】 Recently, due to the features of high load-to-weight-ratio, lightweight and low power consumption etc, flexible joint lightweight robots are widely used in a variety of mobile robots or mechanical platforms, playing a more and more important role in the areas of space exploration, military reconnaissance, counter-terrorism, defusing, as well as home service. From the viewpoint of lightweight robot applications, there exist many different tasks under changing working conditions, either working in dangerous and unknown complex environment or closely contacting with human beings. Therefore, for a safe operation and high reliability, lightweight robots need not only high-precision position control but also compliance control, such that no injury on the robot and operated object will occur when interacting with the unknown environments. Furthermore, the flexibility of the robot joint increases due to the harmonic drive and the torque sensor integrated in the robot joint, which makes the control tasks of lightweight robots to be a challenging issue and results in inevitable vibrations during the robot motion and residual vibrations upon the stopping of the motion. In order to achieve a high control performance, the vibrations must be suppressed. Therefore, Cartesian impedance control as well as vibration (including residual vibration) suppression of flexible joint robots will be investigated deeply, in addition to the study of position control problems.In this work, the hardware system of a flexible joint robot is developed, including mechanical subsystem, sensor subsystem and electronics subsystem; a brief introduction to the electrical layout of the entire system is also given. A 4-DOF lightweight robot was designed based on the idea of modular design with a variety of integrated joint sensors. As a part of the robot system, a lower-level (inner-loop) controller based on Xilinx FPGA, an upper-level (outer-loop) controller based on PCI technique, and a point-to-point-LVDS high-speed serial communication bus between the lower-level and upper-level controllers (with a communication cycle of 200us) were developed as well.The position control of a single-link flexible joint robot based on backstepping approach is realized. However, the traditional backstepping approach is sensitive to the model parameters of controlled system. Therefore, a neural network-based adaptive backstepping controller is employed, which not only overcomes the problem of the sensitivity to the model parameters, but also eliminates the need of accurate dynamic model of the flexible joints robot. Moreover, the control system is not subjected to the restrictions on the range of joint flexibility, and the link acceleration and jerk signals are not required for the control realization. Simulation and experimental results confirmed the effectiveness of the proposed control approach, and at the same time, the repeatability of positioning accuracy of end-point position and attitude is reached according to the design target.We realized Cartesian impedance controller based on backstepping approach to achieve compliance control of the lightweight robot, during which the“explosion of terms”problem associated with the traditional backstepping approach occurs. To overcome this problem, an impedance controller based on the so-called Dynamic-Surface-Control-backstepping is proposed, which introduces a first-order integral filter to estimate the derivative of the virtual control input in each step of the backstepping design process; this action not only eliminates the“explosion of terms”, but also filters out the sensor noise, thus improving the dynamic performance of the system. The effectiveness of this new control approach is confirmed by the compliance behavior of the flexible joint robot working in constrained environments.Finally, vibration and residual vibration due to the joints flexibility (induced by the integrated harmonic drive and joint torque sensor) are suppressed. A joint state observer based on Luenberger approach is designed in order to reconstruct the link-side position and velocity, using motor position and joint torque as the input of the observer. As for the residual vibration upon the stopping of the motion, the time-varying input-shaping technique is introduced.In this thesis, the position control and vibration suppression as well as the residual vibration suppression are realized on the first generation 4-DOF flexible joint lightweight robot. while Cartesian impedance control is implemented on the second-generation 5-DOF flexible joint lightweight robot.更多还原