摘要
应用仿人智能鲁棒性高、能对付难控对象的控制特点,结合模糊RBF神经网络控制技术,提出仿人模糊神经网络控制方法,对PID控制器参数进行优化调节。该方法采用仿人智能的多模态控制思想,对PID控制器的模式进行选择。对非线性系统控制的仿真结果表明,加入仿人控制后,系统从响应速度和上升时间上均有明显提高,具有良好的控制效果。
Human-Simulated Fuzzy Neural Network Control method is proposed, which applies with the performance of the high robust and the performance of dealing with the objects with dificuhy of controlling , combines with fuzzy RBF Neural Network control technology, optimize the parameters of PID controller. The method uses multi-mode control thought of Human-Simulated intelligence, select the mode of PID controller .Simulation results in nonlinear system shows that the control performance of Human-Simulated fuzzy RBF Neural Network is better than the fuzzy RBF Neural Network .
出处
《微计算机信息》
2009年第7期56-58,共3页
Control & Automation
关键词
仿人智能
模糊控制
RBF神经网络
PID控制
仿真
Human-Simulated intelligence
Fuzzy control
RBF Neural Network
PUD control
Simulation
