Abstracts:The goal of this paper is to overview the historical development of the field of Petri nets (PNs) from a Systems Theory and Automatic Control perspective. It is intentionally not meant to be comprehensive: we limit ourselves to outline, through selected representative topics, some of the conceptual issues studied in the literature. In a first part we retrace the emergence of some basic net concepts to provide a broad view of the family of PN formalisms. Then we focus, more specifically, on the use of Petri nets within Automatic Control. Discrete net models have been considered since the middle of the 70s and starting since the late 80s have also been used for addressing classical problems, such as supervisory and deadlock control, state estimation, diagnosis, and so on. The double benefit is the ability to model a larger class of systems and to provide efficient algorithms for solving certain of those problems. We also discuss new approaches based on continuous and hybrid nets, which have been developed within the Automatic Control community.

Abstracts:A novel modelling framework is proposed for the analysis of aggregative games on an infinite-time horizon, assuming that players are subject to heterogeneous periodic constraints. A new aggregative equilibrium notion is presented and the strategic behaviour of the agents is analysed under a receding horizon paradigm. The evolution of the strategies predicted and implemented by the players over time is modelled through a discrete-time multi-valued dynamical system. By considering Lyapunov stability notions and applying limit and invariance results for set-valued correspondences, necessary conditions are derived for convergence of a receding horizon map to a periodic equilibrium of the aggregative game. This result is achieved for any (feasible) initial condition, thus ensuring implicit adaptivity of the proposed control framework to real-time variations in the number and parameters of players. Design and implementation of the proposed control strategy are discussed and an example of distributed control for data routing is presented, evaluating its performance in simulation.

Abstracts:Present researches in power and energy fraternity are driven towards the realization of smart grid (SG) technologies. Microgrids (MGs) being regarded as “elementary units” of SG, has undergone rigorous research for more than one and a half decade now. It provides an integration platform for microsources (MSs), loads, storage devices and power electronics (PE) converters at demand premises forming a system of systems i.e. SoSs architecture. MGs mostly operated in grid-tied mode but during an emergency, are capable of standalone operation. Stability and operational control during both the modes are of utmost concern. Involvement of several control functionalities viz. normalcy of voltage and frequency, optimal power sharing, islanding detection etc., had been adhered in the literature. In spite of that, the real world implementation has not been of significant extent, that too even is far from having ideal MG characteristics, eligible for commercial usage. These technical obstacles need to be identified and dealt with. This paper provides a comprehensive survey of different control aspects of MGs, broadly classified under four control strategies: centralized, decentralized, distributed and hierarchical frameworks. Each scheme is reviewed in detail w.r.t the principles behind, their applicability and performances. It also identifies several research gaps and future trends therein. The technical barriers for real scale application and their solutions are also briefly discussed. And finally, a discussion on different integrated technologies for MGs, to realize SG features is also presented.

Abstracts:In support of the growing interest in how to efficiently influence complex systems of interacting self-interested agents, we present this review of fundamental concepts, emerging research, and open problems related to the analysis and control of evolutionary matrix games, with particular emphasis on applications in social, economic, and biological networks.

Abstracts:Synthetic biology is the application of engineering principles to the fundamental components of biology, with the aim of creating systems with novel functionalities that can be used for energy, environment, and medical applications. While the potential impact of this new technology is enormous, there are challenges that we need to overcome before the impact of synthetic biology can be fully realized. Many of these challenges fall beyond the scope of molecular biology and are indeed “system-level” problems, where very little research is being performed. This paper identifies pressing challenges in synthetic biology that can be formulated as systems and control theoretic problems and outlines potentially new systems and control theories/tools that are required to tackle such problems. The aim is to attract more systems and control theorists to collaborate with molecular biologists and biophysicists and help synthetic biology reach its promise. At the same time, engaging the systems and control community more broadly into the rich research opportunities and life-changing applications of synthetic biology may provide added visibility to the field of systems and controls.

Abstracts:Trajectory planning and trajectory tracking constitute two important functions of an autonomous overtaking system and a variety of strategies have been proposed in the literature for both functionalities. However, uncertainties in environment perception using the current generation of sensors has resulted in most proposed methods being applicable only during low-speed overtaking. In this paper, trajectory planning and trajectory tracking approaches for autonomous overtaking systems are reviewed. The trajectory planning techniques are compared based on aspects such as real-time implementation, computational requirements, and feasibility in real-world scenarios. This review shows that two important aspects of trajectory planning for high-speed overtaking are: (i) inclusion of vehicle dynamics and environmental constraints and (ii) accurate knowledge of the environment and surrounding obstacles. The review of trajectory tracking controllers for high-speed driving is based on different categories of control algorithms where their respective advantages and disadvantages are analysed. This study shows that while advanced control methods improve tracking performance, in most cases the results are valid only within well-regulated conditions. Therefore, existing autonomous overtaking solutions assume precise knowledge of surrounding environment which is not representative of real-world driving. The paper also discusses how in a connected driving environment, vehicles can access additional information that can expand their perception. Hence, the potential of cooperative information sharing for aiding autonomous high-speed overtaking manoeuvre is identified as a possible solution.

Abstracts:This paper provides a brief perspective of academic model-based Fault Detection, Identification and Recovery (FDIR) developments for aerospace and flight systems, and discusses a future paradigm shift in civil aviation operations.

Abstracts:This paper puts forward the comparative performances for synchronisation between (i) systems from different chaotic system families, (ii) systems from the Unified Chaotic System (UCS) family, (iii) a hyperchaotic and a chaotic systems and (iv) identical chaotic systems. Three different well-known control techniques, i.e. Nonlinear Active Control (NAC), Sliding Mode Control (SMC) and Adaptive Control (AC) are used for synchronisation between various pairs of chaotic and/or hyperchaotic systems. Performances of NAC, SMC and AC techniques are investigated and compared with synchronisation of different pairs of chaotic systems based on the error dynamics and required control inputs. The integral square error and required control energy measures are considered for comparison. Finally, a generalised view on the use of the control techniques for synchronisation is finally proposed. Moreover, a new chaotic system is proposed and its qualitative analysis is done to illustrate the chaotic behaviour of the system. The new system is used as an example of synchronisation. MATLAB simulation results are presented which reflect the successful achievement of the objectives.

Abstracts:This brief history summarizes the ‘supervisory control of discrete-event systems’ as it has evolved in the period 1980–2017. Overall, the trend has been from centralized or ‘monolithic’ control to more structured architectures, and from ‘naive’ to symbolic computation. Like any ‘history’ this one represents the perspective of the authors; in consequence some important contributions may have been overlooked or short-changed.

Abstracts:Fields of machine learning and artificial intelligence are undergoing transformative advances and growth. This article presents a vision for the field of systems and control that simultaneously leverages these advances to more fully engage with them and spur new expansive research directions in systems and control.