In this letter a novel deep neural network based integral sliding mode (DNN-ISM) control is
proposed for controlling perturbed systems with fully unknown dynamics. In particular, two …

Electro-hydraulic actuators (EHAs) are key linear drive components in various industrial
applications. This paper addresses the challenge of achieving precise displacement …

In this paper, the combined use of deep neural networks (DNNs) and integral sliding mode
(ISM) control is investigated, giving rise to novel DNN-ISM control strategies for nonlinear …

A model-free fractional-order sliding mode control (MFFOSMC) method based on a non-
linear disturbance observer is proposed for the electric drive system in this paper. Firstly, the …

The three-degree-of-freedom (3-DOF) stabilized control system for ship propulsion-assisted
sails is used to control the 3-DOF motion of sails to obtain offshore wind energy. The attitude …

Model-based control systems allow engineers to leverage known system information in
controllers, often resulting in improved control accuracy or robustness. However, these …

This paper presents an overview of some sliding mode control and observation schemes
based on the joint use of neural networks (NNs) and the so-called integral sliding mode …

This paper proposes an integral sliding mode (ISM) based unknown input observer (UIO)
which is able to perform fault diagnosis (FD) in condition of lack of knowledge of the plant …

This paper proposes an enhanced version of the integral sliding mode (ISM) control, where
a deep neural network (DNN) is first trained as a deep reinforcement learning (DRL) agent …

This research addresses the design of an Adaptive Fuzzy Sliding-Mode Control (AFSMC) for
a group of nonlinear under-actuated systems with unknown input gain functions. In the …