摘要
使用小波神经网络分别逼近对象模型和逆模型,并对原非线性系统及其逆模型组成的伪线性系统采用内模控制理论,基于逆系统方法进行控制。当系统的建模误差满足线性增长条件时,分析了小波神经网络内模控制系统的鲁棒性和稳定性,当系统的建模误差不满足线性增长条件时,应用波波夫超稳定性理论分析了系统的鲁棒性。仿真结果表明小波神经网络内模控制系统是处理非线性问题比较有效的方法之一。
The wavelet network is used to approximate to the nonlinear continuous system and its inverse system. The pseudo-linear system is composed of nonlinear continuous system and its inverse system are combined by the internal model control method based on the inverse system method. When the modeling error satisfies the linear growth condi- tion, the stability and robustness of the closed-loop system are analyzed. The existing modeling errors are analyzed. When modeling errors do not satisfy the linear growth condition, the Popov stability theory is applied to analyze the robustness of the closed-loop system. A simulation is carried out, and simulation results show that the internal model control theory based on wavelet networks is one of available methods for nonlinear systems.
出处
《现代电力》
2009年第1期77-82,共6页
Modern Electric Power
关键词
内模控制
逆系统
小波神经网络
非线性
伪线性系统
internal model control （IMC）
inverse system
wavelet network
nonlinear
pseudo-linear system
