Trajectory generation and tracking control of a multi-level hybrid support manipulator in FAST

The Feed Support System (FSS) of Five-hundred-meter Aperture Spherical radio Telescope (FAST) is a multi-level redundant support manipulator, which consists of a cable driven parallel manipulator, an A–B rotation mechanism and a Gough–Stewart platform. In this article, we report our work on FAST in the following aspects: first, kinematic model and trajectory generation strategy of the FSS are established. Second, considering preventing the pseudo-drag problem of flexible cable and realizing the accurate pose control for the cable driven parallel manipulator, the hybrid position/force control is implemented and validated. Then, the prediction control is adopted in the Gough–Stewart platform to improve the terminal accuracy. Finally, with the 1:15 similarity model of FSS, experiments are carried out to prove the control accuracy of the cable driven parallel manipulator, showing that the terminal error is within 10 mm and the cable tension is kept in the given range. Further experiments on tracking control of the entire FSS illustrate terminal tracking accuracy of the astronomical observation is less than 2 mm, meeting the design requirement. Trajectory generation and tracking control given in this paper lay the foundation for the FAST prototype.     

基于BP神经网络的机械臂轨迹控制研究

针对六自由度机械臂耦合性强、时变、非线性等性能,基于拉格朗日动力学建模方法,文章采用BP神经网络逼近模型,实现高精度轨迹跟踪。该方法根据六自由度机械臂本体采集的数据进行黑箱辨识建模解耦,建模过程采用BP神经网络逼近,提升建模精度、简化建模过程。针对解耦后的系统,还需建立PID闭环控制器进一步实现轨迹跟踪控制。仿真及实验结果表明,基于BP神经网络的PID控制器能够改善系统的鲁棒性和稳定性,并有效抑制抖动。     

Adaptive neuro-fuzzy control of a flexible manipulator

This paper describes an adaptive neuro-fuzzy control system for controlling a flexible manipulator with variable payload. The controller proposed in this paper is comprised of a fuzzy logic controller (FLC) in the feedback configuration and two dynamic recurrent neural networks in the forward path. A dynamic recurrent identification network (RIN) is used to identify the output of the manipulator system, and a dynamic recurrent learning network (RLN) is employed to learn the weighting factor of the fuzzy logic. It is envisaged that the integration of fuzzy logic and neural network based-controller will encompass the merits of both technologies, and thus provide a robust controller for the flexible manipulator system. The fuzzy logic controller, based on fuzzy set theory, provides a means for converting a linguistic control strategy into control action and offering a high level of computation. On the other hand, the ability of a dynamic recurrent network structure to model an arbitrary dynamic nonlinear system is incorporated to approximate the unknown nonlinear input–output relationship using a dynamic back propagation learning algorithm. Simulations for determining the number of modes to describe the dynamics of the system and investigating the robustness of the control system are carried out. Results demonstrate the good performance of the proposed control system.     

复杂背景下兼顾跟踪实时性和跟踪精度的目标跟踪技术研究

由于将CamShift算法在复杂背景和操作条件下应用于视频跟踪,跟踪失败和目标损失的现象将非常容易发生。为了提高复杂环境条件下目标跟踪的精度及实时性,本论文提出了一种能够在复杂环境条件下及时对目标对象进行追踪的技术。以颜色、纹理、目标动作信息的全面特性为基础对CamShift算法作出整改完善,通过组合Kalman过滤器预评估目标对象的动作情况,在目标对象受到制约的情况下,使用运转前的目标对象预先信息,对目标对象物体的动作轨迹执行最小平方运算以及外穿推进,同时基于对象物体的位移情况进行定位信息的预测评估,以助于恢复目标的定位信息直到制约情况结束。经多次实验,相关统计数据表明,这一算法能够用于复杂情形的环境条件下,且当目标对象处于短期闭塞情况下依然能达成目标的连续稳定追踪,在性能上具备出色的实时性。     

Inertial vibration damping control of a flexible base manipulator

A rigid (micro) robot mounted serially to the tip of a long flexible (macro) robot is often used to increase the reach capability, but flexibility in the macro-manipulator can make it susceptible to vibration. A rigid manipulator attached to a flexible but unactuated base was considered as an analogous problem. The interaction forces and torques acting at the base of the robot are used to damp the vibration. Appropriate control gain limits are established to ensure the inertia effects, or those directly due to accelerating the links of the rigid robot, have the greatest influence on the interactions. By commanding the link accelerations out of phase with the base velocity, vibrational energy will be removed from the system. This signal is then added to the rigid robot position controller, providing combined rigid robot position and vibration control of the base.     

Robust learning control of a high precision planar parallel manipulator

End-point positioning accuracy and fast settling time are essential in the motion system aimed at semiconductor packaging applications. In this paper, a novel robust learning control method for a direct-drive planar parallel manipulator is presented. A frequency-domain system identification approach is used to identify the high frequency dynamic of the manipulator. A robust control design method is employed to design a stable, fast tracking response feedback controller with less sensitivity to high frequency disturbance and the control parameters are determined using genetic algorithm. A Fourier-series-based iterative learning controller is designed and used on the feedforward path of the controller to further improve the settling time by reducing the dynamic tracking error of the manipulator. Experimental results demonstrate that the planar parallel manipulator has significant improvements on motion performance in terms of positioning accuracy, settling time and stability when compared with traditional XY-stages. This shows that the proposed manipulator provides a superior alternative to XY-motion stages for high precision positioning.     

Torque sensorless control in multidegree-of-freedom manipulator

A torque sensorless control for a multi-degree-of-freedom manipulator is described. In the method, two disturbance observers are applied to each joint. One is used to realize a robust motion controller. The other is used to obtain a sensorless torque controller. A robust acceleration controller based on the disturbance observer is shown. To obtain the sensorless torque control, it is necessary to calculate the reaction torque when the mechanical system performs a force task. The calculation method for the reaction torque is explained. Then the method is expanded to workspace force control in the multi-degree-of-freedom manipulator. Several experimental results are shown to confirm the validity of the proposed sensorless force controller     

基于PLC机械手控制系统的硬件分析

本系统是基于可编程控制器(PLC)的机械手控制系统。详细论述了该系统的组成、控制方案、驱动方式和硬件设计。给出了系统结构图、方案图和PLC设计接线图。     

Nonlinear computed torque control for a high-speed planar parallel manipulator

A new computed torque (CT)-type controller termed nonlinear CT (NCT) controller is developed and applied to a high-speed planar parallel manipulator. The NCT controller is designed by replacing the linear PD in the conventional CT controller with the nonlinear PD (NPD) algorithm. The stability of the parallel manipulator system with the NCT controller is proven using the Lyapunov theorem, and the proposed controller is further proven to guarantee asymptotic convergence to zero of both tracking error and error rate. The superiority of the proposed NCT controller is verified through the trajectory tracking experiments of an actual high-speed planar parallel manipulator, and the experiment results are compared with the CT controller.     

Adaptive synchronization control of a robotic manipulator operatingin an intelligent workcell

The formulation and implementation of a synchronization control scheme applicable to a robotic workcell is described. Such a workcell typically consists of a conveyor system that transports industrial workpieces, a binary camera to recognize the geometric and other characteristics of the workpiece, and a robotic manipulator that is suitably controlled to direct its end effector to achieve a synchronized rendezvous with the workpiece. Subsequent to a successful rendezvous, the robot may pick up the piece (in pick-an-place operations) or perform such other online operations as assembly, processing, or quality inspection. A methodology to ensure rapid rendezvous with accurate tracking is emphasized. Simulation and implementation results are compared and discussed     

Dynamic modeling and control of a 3-DOF Cartesian parallel manipulator

Dynamic modeling is the basic element for controller design of mechanisms. In this paper, an effective dynamic equation of a 3-DOF translational parallel manipulator for control purpose has been derived by the Lagrange-D’Alembert formulation. The structural properties of the derived dynamic equation were proved so that the vast control strategies developed for the serial counterparts can be easily extended for controlling the CPM (Cartesian parallel manipulator). The derived model also leads to decoupling dynamic characteristics, by which the complexity of the controller design can be significantly reduced. Based on this approach, a model-based computed torque method for positioning control of the CPM is illustrated. Both simulated and experimental results show that the model-based controller can achieve high positioning performance. Furthermore, it is shown that the coupling forces from other limbs play significant roles in the force components of the total dynamics of the CPM.     

Robust control of a planar manipulator for flexible and contactless handling

Many industries require non-contact and flexible manipulation systems, such as magnetic or pneumatic devices. In this paper, we describe a one-degree-of-freedom position control of an induced-air flow surface. This device allows to convey objects on an air cushion using an original aerodynamic traction principle. A model of the system is established and the parameters are identified experimentally. A H_∞ robust controller is designed and implemented on the device in order to control the object position. Experiments with objects of various dimensions and materials are conducted and showed the robustness capabilities of the controller.     

Motion control of a tendon-based parallel manipulator using optimal tension distribution

This paper presents the motion control of a six degree-of-freedom tendon-based parallel manipulator, which moves a platform with high speed using seven cables. To control the motion of the platform along desired trajectories in space, nonlinear feedforward control laws in the cable length coordinates are used. Taking account of the effect of redundancy on actuation, the optimal tension distribution should be considered to the advantage of the control laws. Using a method based on the analysis of the workspace condition, tension constraints and limiting torque constraints of actuators, an analytical solution for optimum tension distribution was found and used to compute the force in each cable for compensation of dynamic errors. It is experimentally demonstrated that the proposed control laws reduce the energy consumption of the actuators and satisfy the path tracking accuracy.     

考虑目标运动状态的激光在线跟踪标刻方法

为了解决传统方法容易受到噪声、光照等因素影响,导致目标检测精度与标刻效果降低的问题,在考虑目标运动状态基础上提出一种激光在线跟踪标刻方法.首先根据激光点构建对应运动模型,并通过迭代计算求解获取出目标运动激光点和实际像素坐标,实现激光对实际目标的自主瞄准,并得出目标运动粗略范围;使用改进粒子滤波法进一步精细定位,由此计算...     

Active vibration control of a flexible one-link manipulator using a multivariable predictive controller

This article presents a new application of model-based predictive controller (MPC) for vibration suppression of a flexible one-link manipulator using piezoceramic actuators. Simulation and experimental studies were conducted to investigate the applicability of the MPC strategy to control vibration of the flexible structure having multiple inputs and multiple outputs (MIMO). The performance of the proposed technique was assessed in terms of level of vibration reduction. The results demonstrated that the proposed predictive control strategy is well suited for multivariable control of vibration suppression on flexible structures.     

Intelligent feedforward control and payload estimation for a two-link robotic manipulator

Conventional model-based computed torque control fails to produce a good trajectory tracking performance in the presence of payload uncertainty and modeling error. The challenge is to provide accurate dynamics information to the controller. A new control architecture that incorporates a neural-network, fuzzy logic and a simple proportional-derivative (PD) controller is proposed to control an articulated robot carrying a variable payload. An off-line trained feedforward (multilayer) neural network takes payload mass estimates from a fuzzy-logic mass estimator as one of the inputs to represent the inverse dynamics of the articulated robot. The effectiveness of the proposed architecture is demonstrated by experiment on a two-link planar manipulator with changing payload mass. Experimental results show that this control architecture achieves excellent tracking performance in the presence of payload uncertainty.     

Neural network impedance force control of robot manipulator

The performance of an impedance controller for robot force tracking is affected by the uncertainties in both the robot dynamic model and environment stiffness. The purpose of this paper is to improve the controller robustness by applying the neural network (NN) technique to compensate for the uncertainties in the robot model. NN control techniques are applied to two impedance control methods: torque-based and position-based impedance control, which are distinguished by the way of the impedance functions being implemented. A novel error signal is proposed for the NN training. In addition, a trajectory modification algorithm is developed to determine the reference trajectory when the environment stiffness is unknown. The robustness analysis of this algorithm to force sensor noise and inaccurate environment position measurement is also presented. The performances of the two NN impedance control schemes are compared by computer simulations. Simulation results based on a three-degrees-of-freedom robot show that highly robust position/force tracking can be achieved in the presence of large uncertainties and force sensor noise     

Position control system of a two degree of freedom manipulator witha passive joint

A method is proposed for controlling the position of a manipulator with passive joints that have holding brakes instead of actuators. In this method, the coupling characteristics of manipulator dynamics are used, and no additional mechanisms are required. The effectiveness of the method was verified by experiments using a prototype manipulator. The prototype is a two-degree-of-freedom, horizontally articulated manipulator. The first axis is an active joint, and the second axis is a passive joint. While the brake of the passive joint is released, the passive joint is indirectly controlled by the motion of the active joint through the use of dynamic coupling. While the brake is engaged, the active joint is controlled. By combining these two control modes, the total position of the manipulator is controlled. The experiments show that use of this method makes the precise positioning of the passive joints possible     

穿销机械手的PLC控制的硬件设计

本文首先介绍了PLC在柔性制造系统穿销机械手的应用,其次阐述了加盖机械手的组成及控制流程。从PLC的控制原理角度,设计了穿销机械手控制流程图、电源系统图、PLC的I/O接口设计及它们的地址分配,经实验验证,达到了预期的控制目的。     

On modeling, identification, and control of a heavy-duty electrohydraulic harvester manipulator

Focuses on modeling, parameter estimation, and control for a heavy-duty electrohydraulic manipulator of a harvester machine. The linear-graph method is implemented in deriving mathematical models for the swing, boom and stick subsystems. Actuation dynamics are subsequently integrated with manipulator dynamics to result in a complete machine model. Identification procedures employed in estimating physical parameters are discussed in detail and key parameter results supplied. Model validation studies show good agreement between model predictions and experiments. A Cartesian controller for the motion of the manipulator end-point is described and response results are presented. It is shown that the obtained response is very good for the purposes of this harvester machine, resulting in very small relative tracking errors.