Switching Control of Nonlinear Systems Based on the Quasi-ARX Model and the SVR Algorithm北大核心CSCD

该文基于改进的含有外部输入项的准线性自回归(准ARX)径向基函数(RBF)网络模型和支持向量回归(SVR)算法,提出了一种非线性切换控制方法.改进的准ARX模型非线性部分采用RBF网络.控制系统设计过程分为三个部分:首先,利用聚类方法确定模型的非线性参数;然后,采用线性SVR算法来解决控制系统的鲁棒性问题;接下来,基于控制误差给出切换判定函数,确定切换律给出控制序列.最后通过数值仿真验证了该方法的有效性.

Switching Control of Nonlinear Systems Based on the Quasi-ARX Model and the SVR Algorithm

A nonlinear switching control method was proposed based on an improved quasilinear autoregressive with exogenous inputs (quasi-ARX) radial basis function (RBF) network model and the support vector regression (SVR) algorithm. The RBF network was chosen as the nonlinear part of the improved quasi-ARX prediction model. The proposed controller design method was divided into 3 steps: firstly, the nonlinear parameters of the model were determined with the clustering method; secondly, the linear SVR algorithm was used to solve the robustness problem of the control system; thirdly, the switching criterion function was given based on the control error, and the control sequence were determined according to the switching law. Finally, a numerical example was given to verify the effectiveness of the proposed method.