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The Design and Stability Study of Double Inverted Pendulum Controller

机译:双倒立摆控制器的设计与稳定性研究

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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.
机译:双倒立摆系统很难达到稳态,需要进行数学模型的模拟和物理控制实验。并且系统对控制器要求更高的性能。因此,将改进的遗传算法引入小波神经网络控制器。经过训练的神经网络具有较少的迭代次数,较小的误差和更好的全局收敛能力。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,具有优良的抗干扰能力,效果满足结构性能要求。

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