With increasing demand for using robotic manipulators in industrial applications, controllers
specific for performing repeatable tasks are required. These controllers must also be robust …

In this article, a robust adaptive learning control strategy for uncertain single-input-single-
output systems in strict-feedback form and controllability canonical form (CCF) is studied. For …

Around 1970 the study of nonlinear control systems took a sharp turn. In part, this was driven
by the hope for a more inclusive theory which would be applicable to various newly …

This paper addresses the issue of real-time control for applications, subject to physical
constraints, involving an energy maximization objective. Typical application areas include …

Position coordination of multi-axis mechanical systems is studied. Under the assumption that
the coordination objective can be represented by smooth functions of the positions of the …

We study the problem of online learning and control in partially observable nonlinear
dynamical systems, where the model dynamics are unknown and the controlling agent has …

The design of output feedback for ensuring global asymptotic stability is a difficult task which
has attracted the attention of many researchers with very different approaches. We propose …

A robust current control approach with disturbance cross-coupling compensation for
permanent magnet synchronous motor drives (PMSM) is proposed in this paper. The …

This article presents a framework to enable a human and robot to perform collaborative
tasks safely and efficiently. It consists of three functions. First, human motion is predicted by …

This paper demonstrates the implementation and performance testing of a Deep
Reinforcement Learning based control scheme used for Dynamic Positioning of a marine …