The control problem of an uncertain n-degrees of freedom robotic manipulator subjected to
time-varying output constraints is investigated in this paper. We describe the rigid robotic …

Two gradient descent based fractional methods are proposed for systems with outliers in this
paper. The outliers in the collected data usually causes biased estimates, resulting in a poor …

In this paper, an adaptive fuzzy neural network (FNN) control scheme is developed for a
class of multipleinput and multiple-output (MIMO) nonlinear systems subject to unknown …

System identification is a key discipline within the field of automation that deals with inferring
mathematical models of dynamic systems based on input-output measurements …

In this paper, we consider distributed optimization design for resource allocation problems
over weight-balanced graphs. With the help of singular perturbation analysis, we propose a …

This paper addresses the identification of finite impulse response (FIR) systems with both
quantized and event-triggered observations. An event-triggered communication scheme for …

Purpose This paper aims to design an event-triggered adaptive prescribed performance
controller for flexible manipulators, with the primary objectives of achieving output …

The Chinese nation has accumulated a lot of precious, rich, and wonderful material and
intangible culture in its historical evolution, but these cultures are facing the problem of …

This study proposes two iterative reweighted (IRE) algorithms for systems whose data are
contaminated by outliers. For the negative effect caused by the outliers, traditional least …

The Hegselmann-Krause (HK) model is a typical self-organizing system with local rule
dynamics. In spite of its widespread use and numerous extensions, the underlying theory of …