基于神经网络滑模控制的智能模块位置控制

Weihai Chen, Gao Yong, Zhen Lu, X. Yuan
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引用次数: 1

摘要

基于模块化机器人的标准智能模块,提出了一种神经网络滑模控制方法。利用神经网络逼近系统状态超平面与到达律之间的函数。采用双曲正切函数代替饱和函数,实现滑模控制的边界法设计。仿真结果表明,系统响应速度快,抗干扰能力强。有效地削弱了神经网络滑模控制的抖振性,解决了传统PID控制方法在变负载等复杂环境和条件下无法解决的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Position Control of a Intelligent Module based on Neural Network Sliding Mode Control
Based on the standard intelligent module of the modular robot, a kind of neural network sliding mode control method is put forward. The neural network is used to approach to the function between the state hyperplane of the system and the reaching law. A hyperbolic tangent function is applied to replace the saturated function in order to realize the boundary method design of the sliding mode control. Simulation results show that system owns quick response and strong antijamming capability. Moreover, the chattering of neural network sliding mode control is weakened effectively, and problems that cannot be solved with the traditional PID control method under complicated environment and conditions such as variable load etc can be solved.
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