Predicting the outcomes of cyber-physical systems with multiple human interactions is a challenging problem. This article reviews a game theoretical approach to address this issue, where reinforcement learning is employed to predict the time-extended interaction dynamics. We explain that the most attractive feature of the method is proposing a computationally feasible approach to simultaneously model

This paper reviews existing works on (deep) reinforcement learning considerations in electric power system control. The works are reviewed as they relate to electric power system operating states (normal, preventive, emergency, restorative) and control levels (local, household, microgrid, subsystem, wide-area). Due attention is paid to the control-related problems considerations (cyber-security, big

Motivated by the increasing availability and quality of miniaturized sensors, computers, and wireless communication devices and given their enormous potential, the use of wireless sensor networks (WSN) has become widespread. Because in many applications of WSNs one is required to estimate at each local sensor unit the state of a system given the measurements acquired by multiple sensors, there has

This paper provides a survey on time-delay approach to networked control systems (NCSs). The survey begins from a brief summary on fundamental network-induced issues in NCSs and the main approaches to the modelling of NCSs. In particular, a comprehensive introduction to time-delay approach to sampled-data and networked control is provided. Then, recent results on time-delay approach to event-triggered

This paper focuses on the algebraic expression of discrete event systems (DES), which bridges the gap between linear control system theory and discrete event system theory. For this purpose, we firstly give an overview of different approaches towards an algebraic description existing in the literature in the area of different classes of DES, such as Petri nets, automata and Boolean networks. After

The nonuniform trial length problem, which causes information dropout in learning, is very common in various control systems such as robotics and motion control systems. This paper presents a comprehensive survey of recent progress on iterative learning control with randomly varying trial lengths. Related works are reviewed in three dimensions: model, synthesis, and convergence analysis. Specifically

This paper presents a bibliographical review of definitions, classifications and applications concerning cyber attacks in networked control systems (NCSs) and cyber-physical systems (CPSs). This review tackles the topic from a control-oriented perspective, which is complementary to information or communication ones. After motivating the importance of developing new methods for attack detection and

Motion control theory applied to multi-rotor aerial vehicles (MAVs) has gained attention with the recent increase in the processing power of computers, which are now able to perform the calculations needed for this technique, and with lower cost of sensors and actuators. Control algorithms of this kind are applied to the position and the attitude of MAVs. In this paper, we present a review of recent

The control of a multiple unmanned aerial vehicle (UAV) system is popular and attracting a lot of attentions. This is motivated by many practical civil and commercial UAV applications. Collision avoidance is the fundamental in motion planning of multi-UAVs, especially for large teams of UAVs. Although several collision avoidance approaches have been reported, there is a lack of highlighting the key

The digital transformation of the production sector is setting the scene for a major industrial change. The need for supporting companies in this transformation is currently covered by several maturity models, generally operationalized through standardized questionnaires, which provide, as an outcome, an assessment of the current maturity stage and a set of general improvement recommendations according

The dynamics of mass reaction kinetics chemical systems is modeled by the Feinberg-Horn-Jackson graph and under the ”zero deficiency assumption”, the behavior of the solutions is well known and splits into two cases: if the system is not weakly reversible there exists no equilibrium, nor periodic solution and if the network is weakly reversible in each stoichiometric subspace there exists only one

In recent years, the ability to accommodate various nonlinearities has become even more important to support systems design and analysis in a broad area of engineering and science. In this line of research, this paper discusses usefulness of the notion of integral input-to-state stability (iISS) in assessing and establishing system properties through interconnection of component systems. The focus

This paper presents a review of finite- and fixed-time convergent algorithms for dynamic systems of various dimensions and relative degrees, with or without disturbances. The review mainly focuses on finite- and fixed-time convergent algorithms, which provide explicit and easily computable upper estimates for the corresponding convergence times. The finite- and fixed-time convergent algorithms are

Blood glucose control algorithms have evolved since the beginnings of the artificial pancreas in diabetes treatment. Although the main problem to solve remains as the regulation of blood glucose into the healthy physiological range, the schemes have evolved over time from on-off schemes to the data-based personalized schemes. The evolution has been in accordance with the understanding of glucose metabolism

The realization problem is fundamental in control systems theory and is well understood for linear systems. The situation is quite different for nonlinear systems with or without time delays. New results are given herein either as an abstract characterization of the class of delay–free nonlinear systems which are known to admit a realization, or by characterizing the existence of a realization for

Infectious diseases are latent threats to humankind killing annually millions worldwide. Disease transmission modeling and control remain a central vexation for science as it involves several complex and dynamic processes. In this paper, multiscale stochastic impulsive models in combination with contact patterns are presented to describe outbreaks and epidemics more accurately. The new families of

Artificial neural networks (ANNs) are considered efficient tools for modeling complex, non-linear processes with uncertain dynamic models. ANNs were originally applied as effective predictors of diverse processes with static dependence on the input-output information. However, when the ANN must be applied to characterize an approximate model of time-dependent input-output relationships, then it is

The performance of most of nowadays control techniques depends on the choices of specific designed parameters. In the past five years, a common approach for solving the issue of finding the best designed parameters have been using metaheuristics optimization techniques. In the present review, we explore the use of the germinal center optimization algorithm (GCO) and its applications in neural identification

This Special Section contains review papers covering the topics of the 15th IFAC Symposium on Control in Transportation Systems (IFAC CTS 2018), held in Savona, Italy on June 6–8, 2018. After a brief introduction on the Special Session aim, the papers in this section are briefly summarised.

Under certain conditions giving priority to trucks at signalized intersections will benefit all vehicles because of elimination of extra delays associated with stop and go trucks due to their size and slow deceleration and acceleration rates. In this paper, we develop, analyse and evaluate a traffic light control system for signalized intersections that takes into account the differences in dynamics

As road transportation energy use and environmental impact are globally rising at an alarming pace, authorities seek in research and technological advancement innovative solutions to increase road traffic sustainability. The unclear and partial correlation between road congestion and environmental impact is promoting new research directions in traffic management. This paper aims to review the existing

Sustainability is a key point in the design and management of mobility and traffic systems, which affects also the development of traffic control strategies for freeway networks. According to sustainability-related concepts, freeway traffic controllers should be devised not only for maximally exploiting the road capacity and decreasing vehicles travel delays, but also for reducing pollutant emissions

Traffic congestion on motorways is a serious threat for the economic and social life of modern society as well as for the environment, which calls for drastic and radical solutions. Conventional traffic management measures, currently applied, are valuable, but face limitations. During the last decades, a variety of vehicle automation and communication systems (VACS) have been developed and deployed

Connected and automated vehicles (CAVs) promise to change the transportation landscape with safer, faster and more energy-efficient mobility. However 100% CAV penetration may never be achieved, raising the question of how to ensure a productive co-existence of CAVs with conventional vehicles. In this paper, we address the problem of optimally controlling CAVs under mixed traffic conditions where both

Computers and automation have revolutionised quality and productivity in many industries, but not in medicine. Healthcare costs are thus growing beyond the ability of society to pay for them, multiplied by the impact of increasingly aging populations, and specifically in the demand placed on intensive care unit (ICU) services. Glycemic control is a core ICU therapy with the potential to reduce both

Mechanical ventilation (MV) is a core life-support therapy for patients suffering from respiratory failure or acute respiratory distress syndrome (ARDS). Respiratory failure is a secondary outcome of a range of injuries and diseases, and results in almost half of all intensive care unit (ICU) patients receiving some form of MV. Funding the increasing demand for ICU is a major issue and MV, in particular

Cardiovascular disease is growing epidemically worldwide, multiplying the impact of increasingly aging populations on intensive care unit (ICU) demand. It is the leading cause of ICU admission, length of stay, mortality and, as a result, cost. Hence, there is a significant need to bring the gains in productivity enabled by automation and control systems technologies, which have arisen in so many sectors

Since they lack insulin-producing β-cells, patients with type 1 diabetes mellitus (T1DM) need to supply their body with insulin from external sources to manage their blood glucose (BG) concentration and mitigate the long-term effects of chronically increased BG levels. The common way of dosing insulin in T1DM is basal bolus therapy. In this method, patients continuously supply their body with a small

Biological motion control paradigms can be analyzed from a control theory point of view and translated to control applications. This paper revises and updates important aspects about the neural control of biped gait based on the Central Pattern Generator (CPG) and provides a controller view, including possible artificial implementations of these controllers. A first aspect to consider is the biological

Neglected tropical diseases (NTDs) are endemic to tropical and subtropical regions in Latin America, Africa and parts of Asia, representing a global public health problem. Despite affecting more than one billion people worldwide, the treatments for these diseases are highly toxic or even nonexistent, and it is usually necessary to treat the symptoms individually, which increases the burden to the healthcare

Electrical Impedance Tomography (EIT) is under fast development, the present paper is a review of some procedures that are contributing to improve spatial resolution and material properties accuracy, admitivitty or impeditivity accuracy. A review of EIT medical applications is presented and they were classified into three broad categories: ARDS patients, obstructive lung diseases and perioperative

Glycaemic control (GC) in the intensive care unit is contentious. Hyperglycaemia, hypoglycaemia, and glycaemic variability are all associated with increased morbidity and mortality. While some studies and physiological evidence suggests GC should benefit hyperglycaemic patients, others show no or negative effects and increased incidence of hypoglycaemia. Interpretation of results is made more difficult

Recently, multiple unmanned vehicles have attracted a great deal of attention as viable solutions to a wide variety of civilian and military applications. Among many topics in the field of multiple unmanned systems, formation control and coordination is of great importance. This paper presents a comprehensive literature review on the strategies and methodologies applied for formation control of multiple

Pursuit of a closed-loop artificial pancreas that automatically controls the blood glucose of individuals with type 1 diabetes has intensified during the past six years. Here we discuss the recent progress and challenges in the major steps towards a closed-loop system. Continuous insulin infusion pumps have been widely available for over two decades, but "smart pump" technology has made the devices

General delay dynamical systems in which uncertainty is present in the form of probability measure dependent dynamics are considered. Several motivating examples arising in biology are discussed. A functional analytic framework for investigating well-posedness (existence, uniqueness and continuous dependence of solutions), inverse problems, sensitivity analysis and approximations of the measures for