In this paper, we present a method to analyze local and global stability in offset-free setpoint
tracking using neural network controllers and we provide ellipsoidal inner approximations of …

This article investigates the local stability and local convergence of a class of neural network
(NN) controllers with error integrals as inputs for reference tracking. It is formally proved that …

In this paper, experimental studies of a decentralized neural network control scheme of the
reference compensation technique applied to control a 2-degrees-of-freedom (2-DOF) …

This work presents a neural network control redesign, which achieves robust stabilization in
the presence of unmodeled dynamics restricted to be input to output practically stable …

We discuss the tracking problem in the presence of unmodelled dynamics, for affine in the
control nonlinear dynamical systems, whose nonlinearities are assumed unknown, using …

Most existing adaptive neural controllers ensure semiglobally uniform ultimately bounded
stability on the condition that the neural approximation remains valid for all time. However …

A method is presented to analyze the stability of feedback systems with neural network
controllers. Two stability theorems are given to prove asymptotic stability and to compute an …

In this paper a neural-network-based control technique is proposed for stabilizing a base-
excited inverted pendulum. The pendulum has two degrees of rotational freedom and the …

This paper introduces deep neural networks (DNNs) as add-on blocks to baseline feedback
control systems to enhance tracking performance of arbitrary desired trajectories. The DNNs …

A new approach to the tracking problem, for affine in the control nonlinear dynamical
systems, whose nonlinearities are assumed to be unknown, is presented in this paper. The …