【摘要】 在圆轨倒立摆摆起过程开环控制律优化算法的基础上,应用高精度多层人工神经网络插值原理,研究了摆起过程的闭环控制方法.以每个时间段上的状态变量和相应的控制变量为输入输出学习样本,建立前馈人工神经网络,构成摆起过程的反馈控制系统.通过仿真与实际控制,表明所研究方法是可行和有效的,并为复杂非线性系统的闭环控制提供了新的思路.更多还原

【Abstract】 With the interpolation principle of high precision multi-layered neural network, a closed-loop control method for swing-up process of circular rail inversed pendulum is investigated based on the optimized open-loop control law. Using the calculating results of state and control variables in open-loop process as standard samples of input and output, a feed-forward neural network is established and a feedback control system for swing-up is closed by the network. Through simulation and practical control, it is obvious that the control method is feasible and efficient. It also provides a new hint for a nonlinear closed control system.更多还原