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BP_xoBox
- 各种BP网络训练样本，如倒立摆，双螺旋线，双积分系统等-A variety of BP network training samples, such as the inverted pendulum, double helix, double-points system, etc.
invertedpendulum
- 倒立摆是一种复杂、时变、非线性、强耦合、自然不稳定的高阶系统，许多抽象的控制理论概念都可以通过倒立摆实验直观的表现出来。基于人工神经网络BP算法的倒立摆小车实验仿真训练模型，其倒立摆BP网络为4输入3层结构。输入层分别为小车的位移和速度、摆杆偏离铅垂线的角度和角速度。隐含层单元数16个。输出层设置为1个输出单元。输入层采用Tansig函数，隐含层采用Logsig函数，输出层采用Purelin函数。用Matlab 6.5数值计算软件对模型进行学习训练，并与线性反馈控制逻辑算法对比，表明倒立摆控制B
GA_BPNN
- 基于遗传算法和BP神经网络控制倒立摆的程序，用遗传算法优化神经网络权值阈值以达到更好的控制效果-Based on genetic algorithm and BP neural network control procedures for the inverted pendulum, with a genetic algorithm neural network weight threshold in order to achieve better control performance
MatlabPPID
- bp神经网络优化PID算法，单级倒立摆，神经网络 PID-bp neural network optimization PID algorithm, single inverted pendulum, neural network PID
shengjingdaolibai
- BP神经网络根据LQR控制固高一级倒立摆，稳定控制及起摆控制-BP neural network based on solid LQR control an inverted pendulum stability control and from the pendulum control