Disturbance observer based path tracking control of robot manipulator considering torque saturation

This paper proposes a path-tracking algorithm to compensate for path deviation due to torque limits. The algorithm uses a disturbance observer with an additional saturation element at each joint of n degrees of freedom (DOF) manipulator to obtain a simple equivalent robot dynamic (SERD) model. This model is represented as an n independent double integrator system and is designed to ensure stability under input saturation. For an arbitrary trajectory generated for a given path in Cartesian space whenever any of the actuators is saturated, the desired acceleration of the nominal trajectory in Cartesian space is modified on-line by using SERD. An integral action with respect to the difference between the nominal and modified trajectories is utilized in the nonsaturated region of actuators to reduce the path error. To verify the effectiveness of the proposed algorithms, real experiments were performed for a two DOF SCARA-type direct-drive arm.     

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.     

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.     

Adaptive incremental sliding mode control for a robot manipulator

An adaptive incremental sliding mode control (AISMC) scheme for a robot manipulator is presented in this paper. Firstly, an incremental backstepping (IBS) controller is designed using time-delay estimation (TDE) to reduce dependence on the mathematical model. After substituting IBS controller into the nonlinear system, a linear system w.r.t. tracking errors is obtained while TDE error is the disturbance. Then, the AISMC scheme, including a nominal controller and an SMC, is developed for the resulted linear system to improve control performance. According to the equivalent control method, the SMC in the AISMC scheme is to handle TDE error. To receive optimal control performance at the sliding manifold, an LQR controller is selected as the nominal controller. The SMC is designed based on positive semi-definite barrier function (PSDBF) since it prevents switching gains from being over/under-estimated, and two practical problems are addressed in this paper: A new PSDBF is designed and conservative (large) setting bounds affecting tracking precision and/or system stability are avoided; An improved PSDBF based SMC is developed where the PSDBF and an adaptive parameter are used simultaneously to regulate switching gains, and the system is still stable when sliding variable occasionally exceeds the predefined vicinity. Moreover, finite-time convergence property of the sliding variable is strictly analyzed. Finally, real-time experiments are conducted to verify the effectiveness of the proposed control method.     

Passivity-based reinforcement learning control of a 2-DOF manipulator arm

Passivity-based control (PBC) is commonly used for the stabilization of port-Hamiltonian (PH) systems. The PH framework is suitable for multi-domain systems, for example mechatronic devices or micro-electro-mechanical systems. Passivity-based control synthesis for PH systems involves solving partial differential equations, which can be cumbersome. Rather than explicitly solving these equations, in our approach the control law is parameterized and the unknown parameter vector is learned using an actor–critic reinforcement learning algorithm. The key advantages of combining learning with PBC are: (i) the complexity of the control design procedure is reduced, (ii) prior knowledge about the system, given in the form of a PH model, speeds up the learning process, (iii) physical meaning can be attributed to the learned control law. In this paper we extended the learning-based PBC method to a regulation problem and present the experimental results for a two-degree-of-freedom manipulator. We show that the learning algorithm is capable of achieving feedback regulation in the presence of model uncertainties.     

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.     

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。     

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     

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     

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。     

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.     

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.     

Design and control of robot manipulator with a distributed actuation mechanism

This paper presents a design methodology based on the distributed actuation principle to achieve a high-performance robot manipulator. Spatial movement of the actuation points provides several advantages such as high payload capacity, high efficiency and a light weight structure for the proposed robot manipulator. Based on the analysis, the distributed actuation mechanism using a single slider is adopted for the proposed manipulator. A prototype of the manipulator with two degrees of freedom is developed and controlled as an example. The efficacy of the proposed approach is verified experimentally.     

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.     

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.     

基于STM32的语音控制机械手

智能机器人技术为近年来研究热点,机械手在智能机器人教学研究与工业机器人领域占据很大比例,本文设计实现了基于STM32为控制平台的四自由度机械手控制系统,系统可以调试,存储机械手动作,并且使用语音控制模块,使机械手具备人机对话,语音控制功能。系统高效,灵活,使用方便,对于智能机器人研究教学,工业机械人控制系统研发具有重大意义