Recently, robotic manipulators have been playing an increasingly critical part in scientific
research and industrial applications. However, modeling of robotic manipulators is …

Robot manipulators are widely used in many fields and play a vital role in the assembly,
maintenance, and servicing of future complex in-orbit infrastructures. They are also helpful in …

In this article, a new neural-network-based sliding-mode control (SMC) of an uncertain robot
is presented. The distinguishing characteristic of the proposed control scheme is that the …

Offshore container crane is a highly under-actuated nonlinear system whereas only two
control inputs are employed for driving six system outputs. Controlling such a system is not …

In this paper, an extreme-learning-machine (ELM)-based robust integral terminal sliding
mode (ITSM) control scheme is developed for a bicycle robot (BR) to achieve balancing …

The output performances of stick-slip piezoelectric actuators strongly depend on the contact
force between the driving unit and the slider. However, quantitative measurement of the …

This paper presents a novel sliding mode (NSMC) to control of a 2-DOF robot manipulator
based on the extended grey wolf optimizer (EGWO). The PD control approach is not robust …

This paper presents the design and implementation of hierarchical sliding mode control
(HSMC) with perturbation estimation (PE) technique on a two-wheeled self-balancing …

This paper proposes a new adaptive neural network integral sliding-mode controller using a
bat algorithm (BA-ANNISMC) to control a biped robot. The conventional integral sliding …

This paper proposes a neural network-based model predictive control (MPC) method for
robotic manipulators with model uncertainty and input constraints. In the presented NN …