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This document is an editorial for a special issue of the International Journal of Robust & Nonlinear Control on the topic of time-delay systems. It provides a historical overview of functional differential equations and highlights the contributions of Nikolay Nikolayevich Krasovskii and Aristide Halanay to the field. The special issue includes 21 research papers covering stability, robustness, observer theory, predictors, and delay-based approaches to partial differential equation models. Each paper is briefly described, covering topics such as stabilization of uncertain systems, sampled-data control for nonlinear systems, observer theory for differential delay systems, sensor fault estimation, and control approaches for vehicular platoons. The summaries aim to provide library patrons with a quick understanding of the papers' contents and their relevance to their research interests. [Extracted from the article]

Qiao et al.21 developed adaptive PID controllers for trajectory tracking of robotic manipulators with uncertainties, which consist of a standard PID controller augmented by an adaptation law. Özbay and Gündes4 addressed the problems of pole placement and delay margin by the design of low-order controllers, including specifically PID controllers. Shi et al.11 considered a so-called dynamic equational PID controller, which augments the derivative control in the PID controller to high-order differentials. For well over a century, from the enabling of early governors to a standard tool in process control, PID (proportional-integral-derivative) control stood out as the most favored method for its unparalleled simplicity, ease of implementation, and cost-effectiveness, and indeed has been an enduring gift to feedback control. [Extracted from the article]

In this paper, we consider a multi-sensor networked control configuration with linear plant which is affected by a bounded additive disturbance. Shared network is used for the communication between sensors and controller. It is assumed that the sensors are prone to abrupt faults, while the controller's input may be updated with a varying time-delay. In order to identify and isolate the sensor(s) providing faulty information, we equip the controller with a set-based detection and isolation routine. Furthermore, in the case when the network induces time-delays, control is performed based on the knowledge we have on the mathematical model of the plant. In the presence of model inaccuracies or disturbance, such a control action may not guarantee satisfying performance of the system. Therefore, a stabilising controller with delay compensation has been designed. The functioning of the proposed control algorithm has been illustrated through an example. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]