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一种用于具有时间延迟的跳跃机器人路径跟踪控制的神经网络控制器。

A neural network controller for the path tracking control of a hopping robot involving time delays.

作者信息

Chaitanya V Sree Krishna, Reddy M Srinivas

机构信息

Department of Mechanical Engineering, Indian School of Mines, Dhanbad - 826 004, India.

出版信息

Int J Neural Syst. 2006 Feb;16(1):47-62. doi: 10.1142/S0129065706000469.

Abstract

In this paper a hopping robot motion with offset mass is discussed. A mathematical model has been considered and an efficient single layered neural network has been developed to suit to the dynamics of the hopping robot, which ensures guaranteed tracking performance leading to the stability of the otherwise unstable system. The neural network takes advantage of the robot regressor dynamics that expresses the highly nonlinear robot dynamics in a linear form in terms of the known and unknown robot parameters. Time delays in the control mechanism play a vital role in the motion of hopping robots. The present work also enables us to estimate the maximum time delay admissible with out losing the guaranteed tracking performance. Further this neural network does not require offline training procedures. The salient features are highlighted by appropriate simulations.

摘要

本文讨论了具有偏置质量的跳跃机器人运动。考虑了一个数学模型,并开发了一种高效的单层神经网络以适应跳跃机器人的动力学,这确保了有保证的跟踪性能,从而使原本不稳定的系统稳定。该神经网络利用了机器人回归器动力学,它根据已知和未知的机器人参数以线性形式表达高度非线性的机器人动力学。控制机制中的时间延迟在跳跃机器人的运动中起着至关重要的作用。目前的工作还使我们能够估计在不损失有保证的跟踪性能的情况下允许的最大时间延迟。此外,该神经网络不需要离线训练过程。通过适当的仿真突出了这些显著特征。

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