DRNN在倒立摆摆起控制中的研究  

Control for swing-up of inverted pendulum based on DRNN

作　　者：谢慕君[1] 杨海蓉[1] 

机构地区：[1]长春工业大学电气与电子工程学院,长春130012

出　　处：《计算机工程与应用》2009年第26期223-225,共3页Computer Engineering and Applications

摘　　要：针对小车一级倒立摆的起摆控制,以DRNN神经网络作为辨识器,在线自适应调整PD控制器的两项参数。在起摆范围相同的情况下,DRNN神经网络控制的倒立摆系统其模型参数变化范围为-50%～30%,传统PD控制倒立摆系统其参数变化范围为-40%～20%。结果表明,基于DRNN神经网络的PD控制器比传统的PD控制器具有较强的抗干扰能力和自适应能力,系统鲁棒性增强,效果明显优于传统的PD控制器。The swing-up control of an inverted pendulum,a Diagonal Recurrent Neural Network（DRNN） is built to identify the system and self-tuning the PD gains.At the same ranges of swing-up,the system parameters ranged from -50% to 30% for selftuning PD control based on DRNN,from -40% to 20% for conventional PD controller.The simulation results show that the system,compared with conventional PD controller,the presented control system has great anti-jamming,adaptability and robustness.

关 键 词：倒立摆 DRNN神经网络 PD控制 摆起 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]