论文部分内容阅读
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.
On the basis of the optimization algorithm of the open-loop control law of the round pendulum swinging process, the closed-loop control method of the swinging process is studied by using the interpolation principle of high-precision multi-layer artificial neural network.According to the state variables and corresponding Of the control variables for the input and output of learning samples, the establishment of feedforward artificial neural network, posing swinging process feedback control system.Through simulation and actual control, shows that the method is feasible and effective, and for closed-loop control of complex nonlinear systems Provide a new way of thinking.