Experimental study of event-based neural network control on parallel manipulator

In the paper, the event-based switching controller (ESC) is utilized to achieve better tracking performance compared with the neural network controller in circumstance of parameter uncertainty and unknown disturbance for the parallel manipulator. The ESC optimizes the choice of the neural weights by combining the prior knowledge of the system dynamics and the estimation of the system parameters. To implement the controller, a general method of computing the system regression matrix for the PM is proposed and the stability proof is given in circumstance of unbounded disturbance. The ESC is tested by the simulated Delta manipulator and the experimental 5R testbed. The results show the effectiveness of the proposed controller.     

Development of a new 4-DOF endoscopic parallel manipulator based on screw theory for laparoscopic surgery

Development of rigid manipulators for Minimally Invasive Surgery (MIS) becomes essential to replace wire driven manipulators which are problematic due to possible cutting of the wire during the surgery. In this paper, a 4-DOF dexterous endoscopic parallel manipulator for MIS is designed and implemented. The manipulator is developed based on the concept of virtual chain and screw theory. The manipulator consists of four links; two links are 2-PUU (each leg consists of one active prismatic joint and two passive hook joints); the other two links are 2-PUS (each leg consists of one active prismatic join, one passive hook joint and one passive spherical joint). The inverse and forward kinematics solutions are derived analytically and numerically, respectively. The singularity analysis is investigated using screws algebra. The manipulator workspace is obtained using MATLAB software. The known problem of limited bending angles found in previous existing surgical manipulators was solved as the proposed manipulator can reach ±90° in any direction. The proposed surgical manipulator is designed, manufactured and tested successfully. The system model utilizing PID and PI controllers has been built using MATLAB software. Co-simulation using ADAMS/MATLAB software is implemented to validate the achieved bending angles and the proposed tracking control. The results show that the performance of the tracking control is satisfactory since the tracking error is about 2.5%.     

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.     

Autonomous and teleoperation control of a mobile robot

The present work proposes an autonomous tracking control system and a control structure to combine autonomous and teleoperation commands in a bicycle-type mobile robot. This compounded operation renders great flexibility to the control system of the mobile robot. For autonomous operation, a simple tracking controller that includes compensation of the robot dynamics is developed. This tracking control system is proved to be stable in the sense that it asymptotically reaches the tracking objective. Teleoperation with visual access to the robot’s workspace is integrated via a joystick with the autonomous operation of the robot. Simulations and experimental results on a prototype robot show the feasibility and performance of the proposed control system.     

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.     

Dynamic trajectory planning study of planar two-dof redundantly actuated cable-suspended parallel robots

This paper analyzes a set of dynamic trajectories for planar two-dof redundantly actuated cable-suspended parallel mechanisms. In recent literature, the global dynamic trajectory planning problem of cable-suspended mechanisms was addressed and some of the characteristic properties of such robots were revealed. In this paper, actuation redundancy is introduced and the dynamic trajectory planning is addressed using a series of periodic trajectories (i.e. straight line and circular periodic trajectories) and the application of the antipodal theorem. The experimental results obtained show that introducing actuation redundancy increases the dynamic capabilities of the robots. Also, cable tensions acquired via tension sensors confirm that cables always remain taut during all experimental verifications at feasible frequencies and that they are consistent with the tension variations predicted by theory. Furthermore, special frequencies are specified that are similar to those encountered with non-redundant mechanisms. Additionally, an alternative architecture is proposed to deal with cable interferences and it is shown that the novel architecture leads to improved dynamic capabilities when compared to the original architecture.     

Error analysis and control scheme for the error correction in trajectory-tracking of a planar 2PRP-PPR parallel manipulator

This paper presents the end-effector pose error modeling and motion accuracy analysis of a planar 2PRP-PPR parallel manipulator with an unsymmetrical (U-shape) fixed base. The error model is established based on the screw theory with considerations of both configuration (geometrical) errors and joint clearances. It also proposes a robust cascaded control scheme for the end-effector pose (task-space) error correction in trajectory-tracking of the manipulator due to mechanical inaccuracies. The proposed control scheme uses redundant sensor feedback, i.e., individual active joint displacements and velocities and, end-effector positions and orientation are obtained as feedback signals using appropriate sensors. To demonstrate the efficacy and show complete performance of the proposed controller, real-time experiments are accomplished on an in-house fabricated planar 2PRP-PPR parallel manipulator.     

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.     

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.     

Industrial robot accurate trajectory generation by nested loop iterative learning control

Common error sources of industrial robot manipulators include joint servoing error, imprecise kinematics, mechanical compliance, and transmission error. In this work we present a nested loop iterative learning control (ILC) feedforward structure: an inner loop that compensates for motor dynamics, and an outer loop that corrects the deviation along the path tracked, that features practically efficient implementation. Taking advantage of industrial robot’s speed reduction transmission, single-input-single-output method is demonstrated effective for the nonlinear coupled robot dynamics. Data-based inversion technique that incorporates motion constraint is used for fast inner loop convergence. The outer loop utilizes inverse Jacobian matrix for joint reference modification. For nonlinear static friction that is difficult to be compensated for with only joint command, notch filtering is utilized in the learning process to avoid exciting vibration inherently exists in the robot. The proposed nested loop ILC requires only the nominal kinematic parameters from the robot manufacturer, and can be readily implemented without modifying the existing robot controllers. The effectiveness of the proposed method is experimentally verified on a six degree-of-freedom robot manipulator.     

A direct torque control algorithm for permanent magnet synchronous motors with minimum torque pulsation and reduced electromagnetic interference noise

In this work, a sensorless hysteresis direct torque control (HDTC) algorithm for a permanent magnet synchronous motor is described. The algorithm uses the output of two hysteresis controllers used in the traditional HDTC to determine two adjacent switching vectors per one sample time. The algorithm also uses the magnitude of the torque error, magnitude of the flux error and stator flux position to select the switching time for the selected vectors. The selection of the switching time utilises table structure which reduces the complexity of calculation. The simulation results of this proposed algorithm show adequate dynamic torque performance and considerable torque ripples reduction as well as lower current ripples and reduced electromagnetic interference noise level, as compared with HDTC.     

多自由度柔性机械手的控制系统实现

本文介绍了一种基于西门子PLC和气动控制设计的多自由度柔性搬运机械手控制系统,实现了柔性自动生产线中两个位置的物料抓取和传送,结构简单、性能可靠、成本低廉,有较强的推广价值.     

An onboard-eye-to-hand visual servo and task coordination control for aerial manipulator based on a spherical model

Compared with the unmanned aerial vehicle (UAV), the aerial manipulator extends the ability to interact with the environment by using the onboard manipulator. The complex dynamic characteristics of the combined system increase the challenges of accurately control the aerial manipulator to approximate the target object. In this paper, an onboard-eye-to-hand visual servo and task coordination control strategy is proposed for the aerial manipulator to enhance the accurate manipulation and flight stability. By establishing a new spherical coordinate error equation, the flying platform (quadrotor) and onboard manipulator can be controlled simultaneously. Meanwhile, the multi-task coordinated control scheme is adopted to achieve precise positioning and grasping of the target object, including estimating the object pose, dynamically compensating the change of the center of gravity of the aerial manipulator, and avoiding the onboard manipulator joint limitations. The stability of the closed-loop system is analyzed by the Lyapunov method. Finally, the feasibility of the proposed visual servo method is verified in simulations and real-world outdoor experiments, respectively. The strengths of the proposed method are demonstrated by comparing it with the conventional visual servo method.     

基于Saber的异步电动机直接转矩控制系统仿真

为了验证基于三电平逆变器异步电动机直接转矩控制系统的可行性和有效性,利用Saber仿真软件优良的模块化和分级式的系统仿真能力,建立了异步电动机直接转矩控制系统中定子磁链与电磁转矩观测器、扇区判断、空间电压开关矢量表以及二极管箝位型三电平逆变器等子系统的仿真模型,并根据直接转矩控制原理最终构建了完整的系统仿真模型。利用所构建的系统仿真模型进行了仿真实验,仿真分析结果证明建立的系统模型是有效的,表明直接转矩控制系统具有良好的动态响应性能。     

Nonlinear tracking control based on extended state observer for vehicle active suspensions with performance constraints

In this paper, a nonlinear tracking control strategy with extended state observer (ESO) is presented for vehicle active suspensions to improve the ride comfort, where suspension spaces, dynamic tire loads are considered as time-domain constraints to be guaranteed. The unique characteristic of the proposed approach lies in the independence on accurate mathematical model. More exactly, the unknown dynamics and external disturbances of the vehicle suspension are regarded as an augmented state of the system and are estimated using the designed ESO. The stability analysis shows that both the estimation error and the tracking error of the control output are bounded and that the upper bounds of the errors monotonously decrease with the increase of the observer bandwidth. Finally, a competitive experiment on a quarter-car suspension prototype is given to demonstrate the effectiveness of the proposed control schemes.     

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.     

Infinite rotational motion generation and analysis of a spherical parallel manipulator with coaxial input axes

This paper presents a novel framework for the analysis of a 3-RRR spherical parallel manipulator with coaxial input axes (coaxial SPM) with the focus on its infinite rotational motion capabilities and its effects on the manipulator’s characteristics. The framework consists of three phases. At first, an approach for obtaining unique solutions of forward and inverse kinematics problems is introduced for setting up univocal relation between coaxial SPM’s input joint positions and orientation of its end-effector. At the second phase, a method for generating infinite rotational motions of an end-effector is formulated. The third phase outlines numerical computation procedures of the coaxial SPM’s workspaces in the joint and Cartesian spaces, excluding singularity configurations and mechanical collisions of SPM’s links during infinite rotational motion. A 3D design model and an experimental prototype of the coaxial SPM is presented and utilized for numerical analysis and experimental verification of the presented framework supplemented by an accompanying video demonstration.     

并联跟踪台单目视觉自标定方法

对并联机构进行标定是实现并联机构几何量校正和高精度定位的前提和基础.目前,现有的自标定方法因得不到完整的并联机构动平台位置和姿态信息,不能满足对并联机构所有几何量进行辨识和标定的要求.针对上述问题,以四自由度并联跟踪台为研究对象,提出了一种新的单目视觉自标定方法,通过实验对其标定精度进行了初步验证,并给出提高标定精度的可行性建议.该方法为并联机床、并联机器人、并联跟踪系统等实现高精度提供了一种新的解决途径.     

Synchronization controller for a 3-R planar parallel pneumatic artificial muscle (PAM) robot using modified ANFIS algorithm

Parallel manipulator is a closed-kinematic chain mechanism in which performance of its end effector – moving platform is contributed by its independent actuators. In traditional designs, each elemental actuator has its own controller as well as reference input, and it works independently without gathering information from its neighbors. Consequently, as one of the actuators cannot keep up with the others, the platform performance is easily deteriorated due to the lack of coherence between these actuators. Therefore, the aim of this paper is to design a 3-R planar parallel robot and develop a proper synchronization controller for its tracking control task. Adaptive Network Based Fuzzy Inference System (ANFIS) algorithm was modified and applied as the main strategy of this synchronization controller. The controller is then able to compensate errors between the actuators and enforce them to cooperate harmonically with each other regardless external disturbances caused by the outside environment or geometrical constraints of the closed-loop structure. Simulations and practical experiments on a scaled parallel robot were carried out to evaluate the designed controller. The results showed that by applying the proposed control technique, the working errors of the component actuators converged quickly to zero almost at the same time. As a result, the tracking performance of the common platform was significantly improved in comparison with the performance when applying a non-synchronization controller. The proposed method is effective in controlling systems which require collaborations between the sub-agents.     

Nonlinear coordination control for a group of mobile robots using a virtual structure

This paper considers the problem of creating a coordination algorithm for a team of mobile robots. The goal for coordinating a group of mobile robots is to create an efficient architecture and control algorithm that enables them to work both individually and in meaningful robot formations. This is achieved by employing coordination and trajectory following techniques, and the knowledge derived by the localization of the robots from their environments.The model use a combination of the Lyapunov technique and graph theory embedded in the virtual structure. In this way, the knowledge derived by the localization of the robots in the group allows for efficient coordination and trajectory following, which can then create useful robot formations.The results obtained from experiments, using three mobile robots in differing formations, show the performance of the controller and the coordination algorithm. They also demonstrate the ability of the algorithm to recover from position sensor measurement errors and temporary delays or failures in the communication, which may cause the robots to momentarily abandon their place in the group formation.