Adaptive proportional-integral H2 sliding mode observer design
WANG Xin-yi
XU Jing
NIU Yu-gang
JIA Ting-gang
Abstract：The observation accuracy of traditional Luenberger observer is easily affected by unknown external distur-bance.To solve this problem,an adaptive proportional-integral H2 sliding mode observer is designed in this paper,which achieves robust exact estimation of nonlinear systems with parameter uncertainties and external disturbances.Firstly,the radial basis function neural network is used to approach the complex nonlinear terms of the system model.Secondly,a linear sliding mode surface based on error is designed,and the proportional integral sliding mode term is injected into the observer,so that the sliding mode dynamic converges to the sliding mode surface in finite time,and the nonlinear compen-sation of external disturbance and system model is realized completely.Finally,an observer parameter self-tuning method is proposed based on the H2 suboptimal control and regional pole assignment.The simulation results of a single-link robot verify the proposed method can ensure the robustness and adaptability of the nonlinear system.
Keywords：sliding mode observerradial basis function networksadaptive controlregional pole assignmentrobust-ness
Publication Date：2023-11-28
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：9( 1940-1948 )