This article investigates the neural-network-based adaptive predefined-time tracking control
problem for switched nonlinear systems. Neural networks are employed to approximate the …

This work focuses on the problem of predefined-time bipartite consensus tracking control for
a class of nonlinear MASs with asymmetric full-state constraints. A predefined-time bipartite …

In this paper, adaptive impedance control is developed for an-link robotic manipulator with
input saturation by employing neural networks. Both uncertainties and input saturation are …

This paper investigates adaptive neural control methods for robotic manipulators, subject to
uncertain plant dynamics and constraints on the joint position. The barrier Lyapunov function …

This article investigates the event-triggered control problem for stochastic nonlinear systems
with unmeasured states and unknown backlash-like hysteresis. Based on the fuzzy logic …

This article investigates the adaptive neural network (NN) finite-time output tracking control
problem for a class of multi-input and multi-output (MIMO) uncertain nonlinear systems …

The issue of neural adaptive self-triggered tracking control for uncertain nonlinear systems
with input hysteresis is considered. Combining radial basis function neural networks …

In this paper, we present adaptive neural network tracking control of a robotic manipulator
with input deadzone and output constraint. A barrier Lyapunov function is employed to deal …

In this paper, the tracking control problem is considered for a class of multiple-input multiple-
output (MIMO) nonlinear systems with input saturation and unknown direction control gains …

This brief is concerned with the finite-time tracking control problem for switched nonlinear
systems with arbitrary switching and hysteresis input. The neural networks are utilized to …