Autonomy has become a focal point for research and development in many industries. Whilst this was traditionally achieved by modelling self-engineering behaviours at the component-level, efforts are now being focused on the sub-system and system-level through advancements in artificial intelligence. Exploiting its benefits requires some innovative thinking to integrate overarching concepts from big

In this paper, we address a scheduling problem belonging to a two-stage assembly system that can also be viewed as a mass customization system. The first stage of this system consists of a set of subassembly machines, each of which produces a component type. These components are then transferred in sublots to Stage 2, where they are assembled into finished products. Stage 2 consists of multiple parallel

This paper formulates a Model Predictive Control (MPC) policy to mitigate the COVID-19 contagion in Brazil, designed as optimal On-Off social isolation strategy. The proposed optimization algorithm is able to determine the time and duration of social distancing policies in the country. The achieved results are based on data from the period between March and May of 2020, regarding the cumulative number

Synchronization pertains to the property of interconnected systems according to which their dynamic behavior is coordinated in an appropriate sense. That is to say, some of their state variables, or functions of the latter for that matter, converge to each other. Synchronization may occur naturally or may be induced, controlled, and it may be present between two systems or among a large number. In

Anti-jerk controllers, commonly implemented in production vehicles, reduce the longitudinal acceleration oscillations transmitted to the passengers, which are caused by the torsional dynamics of the drivetrain during torque transients. Hence, these controllers enhance comfort, drivability, and drivetrain component durability. Although anti-jerk controllers are commonly implemented in conventional production

A key assumption in the development of system identification and adaptive control schemes is the availability of a regression model which is linear in the unknown parameters (of the plant and/or the controller). Applying standard— e.g., gradient descent-based—parameter estimators leads to a linear time-varying equation for the parameter errors, whose stability relies on the usually stringent persistency

Inverse optimal control (IOC) is a powerful theory that addresses the inverse problems in control systems, robotics, Machine Learning (ML) and optimization taking into account the optimal manners. This paper reviews the history of the IOC and Inverse Reinforcement Learning (IRL) approaches and describes the connections and differences between them to cover the research gap in the existing literature

This paper presents a tutorial of the role that mean-field-type games play in the design of risk-aware controllers. The tutorial is presented in an easy-to-follow manner for beginners, engineers and early career scientists. It starts by introducing a basic stochastic mean-field-free control design problem and progressively adds more complexity to the problem setup navigating through the risk-aware

Youla-Kucera (YK) parametrization was formulated decades ago for obtaining the set of controllers stabilizing a linear plant. This fundamental result of control theory has been used to develop theoretical tools solving many control problems ranging from stable controller switching, closed-loop identification, robust control, disturbance rejection, adaptive control to fault tolerant control. This paper

The performance of manufacturing networks relies on interactions. Digitalization supports an evidence-based understanding of partners’ idiosyncrasies and behaviours, so that proper decision-making takes place. Indeed, context uncertainty and flexible problem solving demand human involvement in cyber-physical systems. Therefore, to materialize systems efficiency along with flexibility and robustness

Around 30% to 70% of products in retail and services experience low demand, including spare parts and components for nearly all types of machinery and equipment industries. A detailed analysis of stock forecasting methods for the low demand represents a research gap in inventory management. The existing clustering methods, that is, ABC analysis and XYZ analysis (based on coefficient of variation),

Through the introduction of stochastic operators, the following work is an extension of previous works on robustness and resilience of compartmentalized closed-loop input-output systems. Indeed, those can be subject to the onset of external random perturbations which compromise the functioning of the input-output processing. The stochastic version of the network Price identity shows that the amplified

A manufacturing system able to perform a high variety of tasks requires different types of resources. Fully automated systems using robots possess high speed, accuracy, tirelessness, and force, but they are expensive. On the other hand, human workers are intelligent, creative, flexible, and able to work with different tools in different situations. A combination of these resources forms a human-machine/robot

Despite the enormous benefit that has accrued to society from control technology and the continued vitality of control science as a research field, there is broad consensus that the practitioners of control and the academic research community are insufficiently engaged with each other. We explore this concern with reference to the oft-cited theory/practice gap but also from an industry perspective

The paper presents an improved formula for optimal navigation with respect to time which can be applied to the practical methods and numerical techniques for computing minimum-time paths and routing in arbitary winds, i.e. strong, critical, weak including their combinations, considered on arbitrary modelling surface, thought of as a Riemannian manifold of dimension two. It admits space and time dependence

In the context of the mainstream of globalisation and a new trend of slowbalisation, we review the existing literature including both empirical and analytical papers on the sourcing and location decisions in Supply Chains. After defining the different sourcing strategies, e.g., insourcing, outsourcing, offshoring and reshoring, we present the drivers for each strategy and how they can be incorporated

Due to high computational load of ideal realization of fractional order elements, fractional order transfer functions are commonly implemented via integer-order, limited-band approximate models. An important side effect of such a non-ideal fractional order controller function realization for control applications is that the approximate fractional order models may deteriorate practical performance of

A robust maximum power point tracking (MPPT) control is of paramount importance in the performance enhancement and the optimization of photovoltaic systems (PVSs). Solar panel exhibits nonlinear behavior under real climatic conditions and output power fluctuates with the variation in solar irradiance and temperature. Therefore, a control strategy is requisite to extract maximum power from solar panels

The quest for autonomy has been a pervasive theme in human culture through-out history. In this paper a general definition of autonomous systems is presented and discussed that leads naturally to the establishment of metrics to measure the level of autonomy of a system. This definition is based on the systems ability to achieve goals under uncertainties and it does not involve the means by which the

Motivated by the fact that many nonlinear plants can be represented through Linear Parameter Varying (LPV) embedding, and being this framework very popular for control design, this paper investigates the available Model Predictive Control (MPC) policies that can be applied for such systems. This paper reviews the available works considering LPV MPC design, ranging from the sub-optimal, simplified,

The way humans work in production and logistics systems is changing. The evolution of technologies, Industry 4.0 applications, and societal changes, such as ageing workforces, are transforming operations processes. This transformation is still a “black-box” for many companies, and there are calls for new management approaches that can help to successfully overcome the future challenges in production

Many multi-agent control algorithms and dynamic agent-based models arising in natural and social sciences are based on the principle of iterative averaging. Each agent is associated to a value of interest, which may represent, for instance, the opinion of an individual in a social group, the velocity vector of a mobile robot in a flock, or the measurement of a sensor within a sensor network. This value

We overview a recent research activity where suitable reset actions induce stability and performance of PID-controlled positioning systems suffering from nonlinear frictional effects. With a Coulomb-only effect, PID feedback produces a set of equilibria whose asymptotic (but not exponential) stability can be certified by using a discontinuous Lyapunov-like function. With velocity weakening effects

Aerial manipulators are composed of a robotic arm installed on an unmanned aerial vehicle and are used in several applications because of their inherent ability in performing complex tasks. In real-world applications, these systems are required to be robust against exogenous disturbances, such as wind, to guarantee the desired level of accuracy in the execution of the tasks. In this paper, the reference

This paper presents new perspectives on the application of Artificial Intelligence (AI) solutions to process Spacecraft (S/C) flight data in order to augment currently used operational S/C health monitoring and diagnostics systems. It captures the growing general interest in the usage of such techniques in the Space engineering domain and applications. Jointly with the AI approach, the operational

This paper will review some fundamental results in the understanding of several basic problems concerning feedback and uncertainty. First, we will consider adaptive control of linear stochastic systems, in particular, the global stability and optimality of the well-known self-tuning regulators, designed by combining the least-squares estimator with the minimum variance controller. This natural and

Robotic manipulation aims at combining the versatility and flexibility of mobile robot platforms with manipulation capabilities of robot manipulators. This survey paper comprehensively reviews the state-of-the-art development of collaborative robotic manipulation from the perspective of modelling, control and optimization. Then, the recent results in this field can be categorized into coordination

In this position paper, we summarize history, current activities and future topics of IFAC Technical Committee (TC) 5.2 “Manufacturing Modelling for Management and Control”. As a special focus, we discuss the results of the 9th IFAC Conference MIM 2019 that was recently organized by IFAC TC 5.2 in Berlin, Germany and attended by 740 participants. We analyse the current activities of the working groups

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

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

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

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 have contributed to improve spatial resolution and material properties accuracy, admitivity 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 patients

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