改进随机广义Hammerstein模型的自校正控制器

Self-tuning Controllers for Modified Generalized Hammerstein Model

针对随机广义Hammerstein模型,从实际对象的物理意义出发,分析了广义Hammerstein模型不能描述"对称非线性系统"的问题。在广义Hammerstein模型中加入控制输入的符号函数,提出一可描述"对称非线性系统"的随机广义Hammerstein模型,克服了广义Hammerstein模型要求其控制输入最高阶次为奇数的限制。在目标函数中加入控制输入的高次项和其符号函数,提出一超二次型目标函数。给出一自校正控制器算法,实用于开环不稳定且具有"非最小相位"的系统。仿真研究表明控制算法的有效性。

Based on physical meaning of the practical objective,the problem of Generalized Hammerstein Model（GHM） being not applied to the symmetric nonlinear systems was analyzed in this paper,and a Modified Generalized Hammerstein Model（MGHM） was developed by adding a symbolic function with control input into the GHM,which can overcome the limitation that the maximum order of control input for the GHM has to be odd.A hyper-quadratic object function was given by adding highest order control input term with a symbolic function into the object function,and a self-tuning controller being suitable for the non-minimum phase systems with open-loop unstable characterization was also given.Validation of the control algorithm was demonstrated by the simulated results.