遥操作机器人系统的变时延控制

由于遥操作机器人传输通道中存在着变化的通讯时延,造成了系统不稳定和操作性能降低等问题。为了消除或减少时延的影响,在利用RBF神经网络进行延时预测的基础上,通过改进型Smith预估器进行遥操作机器人的时延控制,从而使系统稳定,并易于操作。理论分析表明,该方案对时延的变化有较强的适应性,控制系统的鲁棒稳定性和动态品质均优于单纯的Smith预估补偿控制,且易于实现。仿真结果表明,在时延情况下,该方法可实现对遥操作机器人较为准确的测控。

Teleoperation Control of an Internet-based Robot with Varying Time Delay

The varying time delay in communication channels of the internet-based robot control system usually leads to instability and bad performance of the system.In order to eliminate or reduce the effect of time delay,an improved Smith predictor to tackle this problem is presented.An RBF (radial basis function) neural network is employed to estimate the time delay of the signal transmission over the Internet.Based on the principle of the Smith predictor,two improved control systems with one Smith predictor and two Smith predictors are respectively presented to deal with the varying time delay.Theoretical analysis and simulation results show that the improved Smith predictor can compensate the varying time delay and ensure the stability and performance.