Self-learning sliding-mode disturbance rejection control for non-affine systems
ZENG Zhe-zhao
WU Liang-dong
YANG Zhen-yuan
TANG Huan
Abstract：Disturbance rejection control (DRC) method with self-learning sliding mode (SLSM) is proposed for a class of single-input single-output (SISO) non-affine nonlinear systems (NANS). The proposed method realizes the extended state estimation of internal parameters perturbation and external disturbances of the NANS based on extended state observer (ESO) designed by nonlinear smooth function. Sliding mode disturbance rejection control (SMDRC) for SISO NANS with uncertainties and disturbance is realized by the technology based on the ESO combined with auto-learning sliding mode control (ALSMC). The method is not dependent on the mathematical model of the controlled plants, and can fast track any given reference signal. Numerical simulation results show that the proposed method not only has fast response, high control precision, but also has strong disturbance-rejection ability for the non-affine nonlinear systems with internal and external disturbance. So the proposed control method will play an important role in control field of the SISO NANS because of its strong robust stability.
Keywords：non-affine nonlinear systems (NANS)sliding mode control (SMC)auto-disturbance rejection (ADR)self-learning control (SLC)nonlinear extended state observer (LNESO)
Publication Date：2016-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：8( 980-987 )