并联机器人的粒子群优化神经网络自适应控制算法研究

针对传统控制算法对并联机器人的控制效果不好的问题,提出了一种并联机器人的粒子群优化神经网络自适应控制算法,该算法在基于神经网络的自适应PID控制算法的基础上,首先对粒子群优化算法进行惯性权重的优化和收缩因子的改进,然后将该改进算法应用于原算法上。仿真试验结果表明,提出的粒子群优化神经网络自适应控制算法,在性能上远远优于传统PID控制算法和基于神经网络的自适应PID控制算法。

基于粒子群优化神经网络自适应控制算法的并联机器人仿真研究

针对传统控制算法对并联机器人轨迹跟踪精度控制效果不好的问题,提出了一种并联机器人的改进粒子群优化神经网络自适应控制算法,首先对粒子群优化算法进行惯性权重的优化和变异操作的改进,然后用改进的PSO算法优化神经网络的初始权值并进行在线调节PID参数。最后以六自由度并联机器人为研究对象,将传统PID控制与基于改进PSO优化的神经网络自适应控制算法分别进行了仿真实验。仿真结果表明,在快速性和稳定性能上,基于改进PSO优化的神经网络自适应控制算法比单纯的PID控制更加优越,在一定程度上减小了轨迹输出的误差并且提高了轨迹跟踪精度。

基于动力学补偿的并联机器人鲁棒轨迹跟踪控制研究

针对6-DOF并联机器人系统存在动力学建模误差和外界不确定性因素干扰的问题,提出了一种基于动力学补偿的并联机器人鲁棒轨迹跟踪控制策略。在充分研究了机器人系统动力学模型特点的基础上,基于Lyapunov方法获得了并联机器人的鲁棒控制率,提出了一种鲁棒轨迹跟踪控制方法,采用逆动力学对内回路进行补偿,外回路采用PD控制,然后对并联机器人进行了鲁棒控制器的设计,最后通过MATLAB进行了系统的轨迹跟踪控制仿真分析。仿真结果表明:当系统存在外界周期干扰的状况时,系统轨迹跟踪误差仍然一致终值有界,在一定程度上提高了系统的鲁棒稳定性。

Synchronous tracking control of 6-DOF hydraulic parallel manipulator using cascade control method

The synchronous tracking control problem of a hydraulic parallel manipulator with six degrees of freedom (DOF) is complicated since the inclusion of hydraulic elements increases the order of the system.To solve this problem,cascade control method with an inner/outer-loop control structure is used,which masks the hydraulic dynamics with the inner-loop so that the designed controller takes into account of both the mechanical dynamics and the hydraulic dynamics of the manipulator.Furthermore,a cross-coupling control approach is introduced to the synchronous tracking control of the manipulator.The position synchronization error is developed by considering motion synchronization between each actuator joint and its adjacent ones based on the synchronous goal.Then,with the feedback of both position error and synchronization error,the tracking is proven to guarantee that both the position errors and synchronization errors asymptotically converge to zero.Moreover,the effectiveness of the proposed approach is verified by the experimental results performed with a 6-DOF hydraulic parallel manipulator.

Modeling and motion control simulation of tendon based parallel manipulator translation mechanism for sensor based high value waste processing

A novel sorting system based on one degree of freedom (DOF) tendon based parallel manipulator (TBPM) for high value waste processing was presented and designed. In order to control the motion of loads, nonlinear state feed forward control algorithm in the tendon length coordinate was used. Considering the system redundancy and actuation behavior, algorithms of optimal tension distribution and forward kinematics were designed. Then, the simulation experiments of motion control were implemented. The results demonstrate that the proposed TBPM translation system performs robust capacities. It can transfer the loads 1 m away within 1.5 s. With further optimization, the translation duration can be further reduced to be about 1 s and the optimized translation is followed with 43.59 m/s2 maximum acceleration. The translation errors at the aim position remain below 0.4 mm.

Hybrid position/force control strategy and experiment of the six-cable driven parallel manipulator for the forty-meter aperture radio telescope

This paper mainly analyzes a hybrid position/force control strategy and experiment of a six-cable driven parallel manipulator for a forty-meter aperture radio telescope. Through the establishments of a kinematic model, a catenary model and a cable-force characteristics model, a basic method is presented based on preventing the pseudo-drag problem of a flexible cable and realizing the hybrid position/force control for a six-cable driven parallel manipulator, and a hybrid position/force control system is developed. Some specific experiments in two typical velocities for astronomical observations are carried out. Experimental results show that the tracking accuracy is related to the speed of the movement. The desired tracking accuracy of the support system is achieved through an effective hybrid position/force control strategy, the cable forces are controlled effectively, and the pseudo-drag problem of flexible cable is solved. This study establishes the foundation of achieving the harmonious movement of the six-cable driven parallel manipulator, A-B rotating platform and the Stewart fine tuninz olatform.

The Design of a Motion Control System for a Parallel Robot with Image Positioning

A motion control system for a parallel robot with image positioning was implemented in this paper. The system is composed of a machine vision device, a delta robot and a linear stage, and the concerned hardware, software and working methods were developed completely and verified successfully. During the phase of machine vision, the image of object was captured by camera, and then the process of smoothing filter, threshold algorithm and edge detection, was applied so as to obtain the edges of image. Finally, DV-GHT （Displacement Vector Generalized Hough Transformation） algorithm was used to recognize the center of multiple and arbitrary 2-D shapes objects. After the center of objects was recognized, the objects were delivered to the workspace of a delta robot by a motorized stage. Through the coordinate transformation between the camera and the robot system, the information of center can be converted to control commands for every working motors. Following, the delta robot picks up objects to the specified position sequentially by the trajectory planning and tracking controls. The software of C＋＋/CLI is used to achieve the phase of motion controls and the program of DV-GHT is used to detect and conduct the positions for four different characteristics of the objects simultaneously so as to indicate the delta robot to classify the objects successfully.