An adaptive control scheme is developed in the paper for nonlinear stochastic systems with
unknown parameters. All the states in the systems are required to be constrained in a …

In this paper, an adaptive controller design is studied for single-input–single-output (SISO)
nonlinear systems with parameter uncertainties and the systems are enforced to subject to …

Robots with coordinated dual arms are able to perform more complicated tasks that a single
manipulator could hardly achieve. However, more rigorous motion precision is required to …

This study introduces a design of robust finite-time controllers that aims to solve the
trajectory tracking of robot manipulators with full-state constraints. The control design is …

This article solves the safe trajectory tracking control problem of robot manipulators with
actuator faults, uncertain dynamics, and external disturbance. Another key issue met in …

This article proposes an adaptive neural network (NN) control method for an-link
constrained robotic manipulator. Driven by actual demands, manipulator and actuator …

In this article, the adaptive neural backstepping control approaches are designed for
uncertain stochastic nonlinear systems with full-state constraints. According to the symmetry …

This article concentrates on the event-driven controller design problem for a class of
nonlinear single input single output parametric systems with full state constraints. A varying …

In this paper, an adaptive neural network (NN)-based tracking control algorithm is proposed
for the wheeled mobile robotic (WMR) system with full state constraints. It is the first time to …

The problem of designing an analytical gain tuning and stable PID controller for nonlinear
robotic systems is a long-lasting open challenge. This problem becomes even more intricate …