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Developments in sensor and processor sophistication have created a need for effective estimation and control algorithms for hybrid, nonlinear systems. This book presents an effective, flexible family of estimation algorithms that can be used in estimating or controlling a variety of nonlinear plants. Several applications are studied, including tracking a manoeuvring aircraft, automatic target recognition, and the decoding of signals transmitted across a wireless communications link. The authors begin by setting out the necessary theoretical background and then develop a practical, finite-dimensional approximation to an optimal estimator. Throughout the book, they illustrate theoretical results by simulation of control and estimation in real-world hybrid systems, drawn from a variety of engineering fields. The book will be of great interest to graduate students and researchers in electrical and computer engineering. It will also be a useful reference for practising engineers involved in the design of estimation, tracking or wireless communications systems.
This monograph provides a tool-set for hybrid estimation that can successfully monitor the behavior of complex artifacts with a large number of possible operational and failure modes such as production plants, automotive or aeronautic systems, and autonomous robots. For this purpose, ideas from the fields of System Theory and Artificial Intelligence are taken and hybrid estimation is reformulated as a search problem. This allows to focus the estimation onto highly probably operational modes, without missing symptoms that might be hidden among the noise in the system. Additionally a novel approach to continue hybrid estimation in the presence of unknown behavioral modes and to automate system analysis and synthesis tasks for on-line operation are presented. This leads to a flexible model-based hybrid estimation scheme for complex artifacts that robustly copes with unforeseen situations.
Hybrid systems have been widely studied in the literature and became a powerful tool for modeling systems coming from many engineering fields. A common definition of hybrid systems is a combination of both continuous-time and discrete event systems. Examples of hybrid systems include networks, multi-agent systems, mechanical devices, robot path planning, biological systems. Researches on hybrid systems cover all fields of control theory such as stability analysis, control and observation problems or supervision. In the context of switched systems, which is a particular class of hybrid systems, this thesis aims at studying the problem related to extracting information about the system parameters and the state from the knowledge of the output.This study is motivated by various purposes: modeling, monitoring, fault detection and identification for the systems safety, output feedback control. For those reasons,the identification and the observation are at the core of decision and control problems.The first part of the thesis is devoted to extend the applicability of the algebra-based methods for on-line constant parameter estimation, developed by INRIA - Non-A project-team, to the case of systems with piecewise constant parameters. To this end, a procedure for the estimation of the parameters and the switching times is developed in the framework of switched systems.Such an approach enables a simultaneous algebraic estimation of both parameters and change time instants. The novelty and efficiency of the proposed identification algorithms mainly lie in their non asymptotic nature. The second part of the thesis addresses the problem of observer design for estimating the discrete and the continuous state of switched systems.Since switched systems contain a family of continuous-time systems and discrete-event systems, the evolution of their dynamics is naturally non-smooth, and this increases the difficulties to solve the observation problem. For instance, the estimates have to be provided before the next switch takes place. Thus, we propose an observer based on finite-time techniques (sliding-mode based) for the reconstruction of the continuous states and the switching signal (discrete state) in finite-time. Finally, we deal with another class of switched systems where the parameters, in each subsystem, are time-varying. For this kind of models, called switched linear parameter varying systems, we design an estimator for reconstructing the discrete state, by using parameter identification techniques.
​Hybrid System Identification helps readers to build mathematical models of dynamical systems switching between different operating modes, from their experimental observations. It provides an overview of the interaction between system identification, machine learning and pattern recognition fields in explaining and analysing hybrid system identification. It emphasises the optimization and computational complexity issues that lie at the core of the problems considered and sets them aside from standard system identification problems. The book presents practical methods that leverage this complexity, as well as a broad view of state-of-the-art machine learning methods. The authors illustrate the key technical points using examples and figures to help the reader understand the material. The book includes an in-depth discussion and computational analysis of hybrid system identification problems, moving from the basic questions of the definition of hybrid systems and system identification to methods of hybrid system identification and the estimation of switched linear/affine and piecewise affine models. The authors also give an overview of the various applications of hybrid systems, discuss the connections to other fields, and describe more advanced material on recursive, state-space and nonlinear hybrid system identification. Hybrid System Identification includes a detailed exposition of major methods, which allows researchers and practitioners to acquaint themselves rapidly with state-of-the-art tools. The book is also a sound basis for graduate and undergraduate students studying this area of control, as the presentation and form of the book provides the background and coverage necessary for a full understanding of hybrid system identification, whether the reader is initially familiar with system identification related to hybrid systems or not.
This book constitutes the refereed proceedings of the 10th International Conference on Hybrid Systems: Computation and Control, HSCC 2007, held in Pisa, Italy in April 2007. Among the topics addressed are models of heterogeneous systems, computability and complexity issues, real-time computing and control, embedded and resource-aware control, control and estimation over wireless networks, and programming languages support and implementation.
This book constitutes the refereed proceedings of the 8th International Workshop on Hybrid Systems: Computation and Control, HSCC 2005, held in Zurich, Switzerland in March 2005. The 40 revised full papers presented together with 2 invited papers and the abstract of an invited talk were carefully reviewed and selected from 91 submissions. The papers focus on modeling, analysis, and implementation of dynamic and reactive systems involving both discrete and continuous behaviors. Among the topics addressed are tools for analysis and verification, control and optimization, modeling, engineering applications, and emerging directions in programming language support and implementation.
This book constitutes the refereed proceedings of the 11th International Conference on Hybrid Systems: Computation and Control, HSCC 2008, held in St. Louis, MO, USA, in April 2008. The 42 revised full papers and 20 revised short papers presented were carefully reviewed and selected from numerous submissions for inclusion in the book. The papers focus on research in embedded, reactive systems involving the interplay between symbolic/switching and continuous dynamical behaviors and feature the latest developments of applications and theoretical advancements in the design, analysis, control, optimization, and implementation of hybrid systems, with particular attention to embedded and networked control systems.
This volume contains the proceedings of the Fourth Workshop on Hybrid - stems: Computation and Control (HSCC 2001) held in Rome, Italy on March 28-30, 2001. The Workshop on Hybrid Systems attracts researchers from in- stry and academia interested in modeling, analysis, synthesis, and implemen- tion of dynamic and reactive systems involving both discrete (integer, logical, symbolic) and continuous behaviors. It is a forum for the discussion of the - test developments in all aspects of hybrid systems, including formal models and computational representations, algorithms and heuristics, computational tools, and new challenging applications. The Fourth HSCC International Workshop continues the series of workshops held in Grenoble, France (HART’97), Berkeley, California, USA (HSCC’98), N- megen, The Netherlands (HSCC’99), and Pittsburgh, Pennsylvania, USA (HSCC 2000). Proceedings of these workshops have been published in the Lecture Notes in Computer Science (LNCS) series by Springer-Verlag. In line with the beautiful work that led to the design of the palace in which the workshop was held, Palazzo Lancellotti in Rome, resulting from the col- boration of many artists and architects of di erent backgrounds, the challenge faced by the hybrid system community is to harmonize and extract the best from two main research areas: computer science and control theory.
This book constitutes the refereed proceedings of the 5th International Workshop on Hybrid Systems: Computation and Control, HSCC 2002, held in Stanford, California, USA, in March 2002. The 33 revised full papers presented were carefully reviewed and selected from 73 submissions. All current issues in hybrid systems are addressed including formal models and methods and computational representations, algorithms and heuristics, computational tools, and innovative applications.