摘要
针对逆变系统负载适应性能不强、动静态性能不佳的特点,设计出一种基于神经网络内模原理的逆变系统控制方法。通过对该方案的理论分析,得出了控制系统的实现方法。通过相应的仿真研究对其策略特性进行分析和比较。与传统控制方式相比较,这种智能控制不依赖于被控对象。由神经网络实现对系统的智能控制,提高了系统的逆变波形质量和负载适应性,使系统获得了较好的动态和稳态性能。
Inverter system load for performance is not strong. To adapt to the dynamic and static poor performance characteristics, design a kind of controll method based on neural network model princi- ple was given, through the analysis of algorithm wave theory, and the control strategy was the realization method of the corresponding simulation and research. The characteristics of strategy were analyzed and compared. With intelligent control relative to traditional control mode, the biggest advantage is that it dosn＇t rely on the mathematical model of the controlled objects, and imitates the processing power of in- formation. The system also gains good dynamic and static performance, improves the efficiency of the system of quality and loads waveform inverter adaptability.
出处
《陕西理工学院学报（自然科学版）》
2012年第1期15-19,共5页
Journal of Shananxi University of Technology:Natural Science Edition
基金
四川省教育厅科研项目(11ZB268)
四川文理学院重点项目(2011Z004Z)
关键词
神经网络
内模
逆变系统
波形控制
neural networks
internal model
inverter system
waveform control
