Control and systems engineering

The latest publications in this offer are:

• May 10, 2025

  S7254

  Petri nets – Theory and implementation

  This article presents the formal and applicative aspects of Petri nets (RdP). This is a tool for modeling and analyzing systems in the formof states, transitions and tokens, in which control evolves asynchronously and concurrently. The concept of token is used to represent capacity. Various extensions to RdP are discussed, offering greater functional expressiveness and more compact modeling. Another type of extension involves the incorporation of time. These extensions make it possible to introduce the notions of urgency, watchdog and duration. Finally, a set of application tools is presented for modeling, simulation and code generation.

• December 10, 2024

  S7439

  Time-Delay Systems

  Delays are common in science and engineering, arising from transmission, propagation, and memory pheno- mena. In control theory, delays can cause instability, oscillations, and bandwidth limitations, requiring careful consideration.This article introduces delay systems using functional differential equations, generalizing ordinary differential equations. It covers stability analysis methods for such systems in frequency and time domains, focusing on computationally verifiable conditions. It also addresses control design challenges, emphasizing computational methods. Examples, code snippets, and references are provided for illustration and further study.

• November 10, 2024

  S7442

  Fixed-time and finite-time control and estimation

  This tutorial presents an introduction to the analysis and design of systems with finite/fixed-time convergence. The main attention is paid to finite-time and fixed-time convergent dynamics. Two large groups of approaches to the analysis/synthesis of this type of convergence are described: based on Lyapunov functions and the theory of homogeneous systems. Some popular control and estimation algorithms, which have accelerated convergence rates, are reviewed. The discretization problems of finite/fixed time convergent systems are discussed. All given results are illustrated by simple examples (scalar or planar).

• October 10, 2024

  S7221

  Identification using physics-driven neural networks

  on the identification of parameters of a system of equations that describes the behavior of a physical phenomenon. The methods called "Physics-Informed Neural Network" and "Physics Constrained Learning" with respective acronyms PINN and PCL, based on the so-called physics-driven neural networks, are firstly presented in a general context and secondly explained and tested in the case of a first-order ordinary differential equation governing for instance the charging of a capacitor. The physicalparameter considered, representing the capacitance, is assumed to be constant or time-varying.

• September 10, 2024

  S7467

  Symbolic approaches to the control of nonlinear systems

  This article deals with controller synthesis for nonlinear systems subject to constraints on states and control, as well as bounded disturbances, and for specifications such as safety, reachability, or more complex properties formulated using automata or temporal logics. In this context, symbolic approaches, based on the abstraction of the system through a symbolic model (with a finite number of states and controls), enable the automatic synthesis of controllers certified as “correct by construction.” This article presents in a didactic manner the key elements of these approaches (abstraction, synthesis, and concretization of controllers) and provides an overview of advanced themes in this dynamically evolving research field.

• May 10, 2024

  S7453

  Analysis and control of PDE systems

• April 10, 2024

  S7186

  Bifurcation structures in nonlinear discrete-time systems

• September 10, 2023

  S7809

  Magneto-inertial navigation

• January 10, 2023

  S7438

  Event-triggered control

  Event-triggered control consists in transmitting data between the system and its controller according to the current state of the system and the desired control objectives. This paradigm is motivated by scenarios where the communication or the computation resources available for the implementation of the controller are limited, such as in networked control systems and embedded systems. This article provides an introduction to the field. Fundamental event-triggered control techniques are presented, their properties are discussed and a robotic experimental validation is provided.

• January 10, 2023

  S7434

  Overview of hybrid dynamic systems

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