Abstract: In order to enhance the stiffness and kinematic performance of 4D interactive stereo game simulation platform, the 3RPS/UPS parallel robot with redundant structure is applied. Firstly, this paper introduces the structure of 3RPS/UPS parallel mechanism and analyzes the inverse kinematics. Then, in view of the shortcomings of traditional PID control in the control precision, this paper proposes a back-stepping control of the state observer based on the RBF neural network. Finally, MATLAB is used to model and simulate the system, and the back-stepping control is compared with the traditional PID control and general neural network adaptive control. The simulation results show that estimating the system state according to the RBF neural network observer and designing the controller with the back-stepping control theory can achieve good state observation as well as the location tracking without velocity signal. This control strategy can improve the accuracy to a certain extent, and its overall control effect is better than the traditional PID controller. Compared with the general RBF neural network adaptive control, the method also has some improvement.

Key words: redundant driving chain, 3RPS, neural network observer, back-stepping?control

摘要： 为了增强4D互动立体游戏仿真模拟平台的刚度和运动性能，将带冗余结构的3RPS/UPS并联机器人应用其中。首先对其结构进行介绍及逆运动学分析，然后针对传统PID控制在控制精度方面的不足，提出了一种基于神经网络观测器的反演控制方法。最后利用MATLAB对其进行建模以及系统仿真实验，并与传统PID控制以及一般的RBF神经网络自适应控制进行对比。由仿真结果可以看出，根据RBF神经网络观测器估计系统状态值，并应用反演控制理论设计控制器，能实现很好的状态观测，从而实现无需速度信号的位置跟踪。该方法也能够在一定程度上提高精度，且其整体控制效果优于传统PID控制器，相比于一般的RBF神经网络自适应控制也有了一定的改进。

关键词: 冗余支链, 3RPS, 神经网络观测器, 反演控制