搜索资源列表
fuzzypid
- 在matlab环境下编程实现了应用模糊控制理论整定PID控制器参数,并对已知模型进行阶跃响应仿真实验。
elman6
- 基于ELMAN神经网络对阶跃响应动态进行补偿也可以举一反三的运用于ELMAN网络的其他应用-Elman neural network based on the step response of the dynamic compensation can be applied to an example of the Elman network other applications
fs
- 模糊控制与PID控制比较,模糊控制仿真的阶跃响应-fuzzy control
MATLAB
- 二阶系统对时域响应性能的影响,单位负反馈系统的单位阶跃响应曲线-Second-order system on the performance of time domain response unit of the negative feedback system unit step response curve
Model-predictive-control
- 预测控制系统频应响应系统分析工具和专用绘图函数,予详细介绍,以一基于阶跃响应模型的控制器设计(动态矩阵控制方法)为例进行示范说明。-Model predictive control
BP_PID
- 神经网络PID控制的阶跃响应,能够准确跟踪输入信号,各项指标满足要求。-the step response of Neural network PID control,Can accurately track the input signal, the indicators meet the requirements.
exp_pid
- 专家pid控制的阶跃响应,能够很好的跟踪输入信号。具有良好的性能指标。-step response of Expert pid control , and can be very good to track the input signal.With good performance。
FUZZY_PID
- 模糊PID控制的阶跃响应,并与PID控制进行对比,验证了模糊PID控制的有效性。-The step response of fuzzy PID control, and compared with PID control, verify the effectiveness of the fuzzy PID control.
