Disturbance Observer-Based Adaptive Integral Sliding Mode Modified Generalized Repetitive Control Method

This article presents a control strategy that combines a disturbance observer-based adaptive integral sliding mode controller (DOB-AISMC) with a modified generalized repetitive controller (MGRC) to address the periodic reference tracking problem in nonlinear systems. The AISMC compensates only for the estimation error of the disturbance observer, not the unknown nonlinearity; therefore, the switching term of AISMC is reduced and chattering is effectively suppressed. The MGRC uses a dual-gain adjustment mechanism to adjust control and learning in repetitive control, thus enhancing the tracking accuracy for periodic signals. It also compensates for magnitude distortion and phase shift caused by the low-pass filter, significantly enhancing steady-state tracking performance. To improve gain tuning efficiency and increase flexibility in controller design, two error-independent performance indices are designed. These indices, derived through recursive iteration and the solution of matrix differential equations, provide direct insights into the influence of controller gains on system performance, eliminating the need for simulation or experimental error evaluation. Simulation and experimental results validate the superior control performance of the presented method.