双倒立摆控制器的设计与稳定性研究

Song Qing-kun, Li Dong-wei
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引用次数: 3

摘要

双倒立摆系统难以达到稳态,对其进行了数学模型仿真和物理控制实验。系统对控制器的性能提出了更高的要求。为此,将改进的遗传算法引入到小波神经网络控制器中。训练后的神经网络具有迭代次数少、误差小、全局收敛能力强等特点。仿真和实际控制实验结果表明,基于改进遗传算法的小波神经网络控制器可以实现对双倒立摆系统的稳定控制,具有优异的抗干扰能力,效果满足结构性能要求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Design and Stability Study of Double Inverted Pendulum Controller
The double inverted pendulum system is hard to reach steady state, the mathematical model before the simulation and physical control experiment. And the system requires higher performance to the controller. So the improved genetic algorithm is introduced into the wavelet neural network controller. The trained neural network has less number of iterations, smaller error and better global convergence ability. The simulation and actual control experiment results show that, the wavelet neural network controller based on the improved genetic algorithm can achieve stable control of the double inverted pendulum system, It has excellent interference resistance ability and effect meet the requirement of structural performance.
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