摘要
两轮自平衡机器人系统是一个高阶次,不稳定,非线性,多变量,强耦合的系统。系统采用Lagrange方程进行动力学建模,将神经网络自组织算法应用于此模型,并对两轮机器人的平衡和速度进行控制,其难点是对车体速度和车轮速度的控制。本文采用神经网络自组织算法,使输出准确地跟踪输入,使机器人按照指定的移动速度和转动速度运动。将该算法与OBS算法相比较,仿真实验结果表明,自组织算法使系统的跟踪速度更快,具有较高的实用价值。
In view of the two - wheeled self - balancing robot system is a high order, instability, nonlinear, multivariable, strong coupling system, mechanical model is established by using Lagrange equation, the selforganizing neural network algorithm is applied to this model, the balance of the two rounds of the robot and speed is controlled. A self - organizing neural network algorithm is used to make the output accurately track the input and make the robot move according to the specified speed and rotational speed, such that the balance of the body and the pendulum. Simulation results show that the proposed self - organizing algorithm has high stability and good tracking performance.
出处
《计算机仿真》
CSCD
北大核心
2015年第4期325-329,共5页
Computer Simulation
基金
国家自然科学基金(61203343)
河北省自然基金(E2014209106)
关键词
两轮自平衡机器人
自组织算法
速度跟踪
神经网络
Two -wheeled self- balancing robot
Self- organization algorithm
Speed tracking
Neural network
