An adaptive sliding mode control (ASMC) based on improved linear extended state observer (LESO) is proposed for nonlinear systems with unknown and uncertain dynamics. An improved LESO is designed to estimate total disturbance of the uncertain nonlinear system, and an interval type-2 fuzzy neural network (IT2FNN) is used to optimize and approximate the observe bandwidth of LESO, and the adaptive parameter tuning is realized based on the gradient descent (GD) method. Based on the total disturbance estimated by LESO, an ASMC strategy is designed to ensure the system stability. By adapting the sliding mode gain, the observation performance of LESO compared to the total disturbance can be better utilized, and system chattering is reduced. Finally, some simulation results are given which show that the proposed control strategy has a good control effect, strong practicability, and wide versatility.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.