This book is used at the graduate or advanced undergraduate level and many others. Manned and unmanned ground, aerial and marine vehicles enable many promising and revolutionary civilian and military applications that will change our life in the near future. These applications include, but are not limited to, surveillance, search and rescue, environment monitoring, infrastructure monitoring, self-driving cars, contactless last-mile delivery vehicles, autonomous ships, precision agriculture and transmission line inspection to name just a few. These vehicles will benefit from advances of deep learning as a subfield of machine learning able to endow these vehicles with different capability such as perception, situation awareness, planning and intelligent control. Deep learning models also have the ability to generate actionable insights into the complex structures of large data sets. In recent years, deep learning research has received an increasing amount of attention from researchers in academia, government laboratories and industry. These research activities have borne some fruit in tackling some of the challenging problems of manned and unmanned ground, aerial and marine vehicles that are still open. Moreover, deep learning methods have been recently actively developed in other areas of machine learning, including reinforcement training and transfer/meta-learning, whereas standard, deep learning methods such as recent neural network (RNN) and coevolutionary neural networks (CNN). The book is primarily meant for researchers from academia and industry, who are working on in the research areas such as engineering, control engineering, robotics, mechatronics, biomedical engineering, mechanical engineering and computer science. The book chapters deal with the recent research problems in the areas of reinforcement learning-based control of UAVs and deep learning for unmanned aerial systems (UAS) The book chapters present various techniques of deep learning for robotic applications. The book chapters contain a good literature survey with a long list of references. The book chapters are well written with a good exposition of the research problem, methodology, block diagrams and mathematical techniques. The book chapters are lucidly illustrated with numerical examples and simulations. The book chapters discuss details of applications and future research areas.

This book provides a new approach to the control of food transformation processes, emphasizing the advantage of considering the system as a multivariable one, and taking a holistic approach to the decision-making process in the plant, considering not only the technical but also the economic implications of these decisions. In addition, it presents a hierarchical structure for the global control of the plant, and includes appropriate techniques for each of the control layers. The book addresses the challenges of modeling food transformation processes, using both traditional system-identification techniques and, where these prove impractical, models based on expert knowledge and using fuzzy systems. The construction of optimal controllers for each of these types of models is also discussed, as a means to close a feedback loop on the higher-level outputs of the process. Finally, the problem of production planning is covered from two standpoints: the traditional batch-sizing problem, and the planning of production throughout the season. Systematic season-wide production planning is built upon the models constructed for the control of the plant, and incorporates market- and business-specific information. Examples based on the processing of various foodstuffs help to illustrate the text throughout, while the book's closing chapter presents a case study on advances in the processing of olive oil. Given its scope, the book will primarily be of interest to two groups of readers: food engineering practitioners and students, who are familiar with the characteristics of food processes but have little or no background in control engineering; and control engineering researchers, students and practitioners, whose situation is just the opposite, and who wish to learn more about food engineering and its specific challenges for control. Advances in Industrial Control reports and encourages the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.

Nonlinear Industrial Control Systems presents a range of mostly optimisation-based methods for severely nonlinear systems; it discusses feedforward and feedback control and tracking control systems design. The plant models and design algorithms are provided in a MATLAB (R) toolbox that enable both academic examples and industrial application studies to be repeated and evaluated, taking into account practical application and implementation problems. The text makes nonlinear control theory accessible to readers having only a background in linear systems, and concentrates on real applications of nonlinear control. It covers: different ways of modelling nonlinear systems including state space, polynomial-based, linear parameter varying, state-dependent and hybrid; design techniques for nonlinear optimal control including generalised-minimum-variance, model predictive control, quadratic-Gaussian, factorised and H design methods; design philosophies that are suitable for aerospace, automotive, marine, process-control, energy systems, robotics, servo systems and manufacturing; steps in design procedures that are illustrated in design studies to define cost-functions and cope with problems such as disturbance rejection, uncertainties and integral wind-up; and baseline non-optimal control techniques such as nonlinear Smith predictors, feedback linearization, sliding mode control and nonlinear PID. Nonlinear Industrial Control Systems is valuable to engineers in industry dealing with actual nonlinear systems. It provides students with a comprehensive range of techniques and examples for solving real nonlinear control design problems.

This monograph presents new algorithms for formation control of multi-agent systems (MAS) based on principles of continuum mechanics. Beginning with an overview of traditional methods, the author then introduces an innovative new approach whereby agents of an MAS are considered as particles in a continuum evolving in n whose desired configuration is required to satisfy an admissible deformation function. The necessary theory and its validation on a mobile-agent-based swarm test bed are considered for two primary tasks: homogeneous transformation of the MAS and deployment of a random distribution of agents on a desired configuration. The framework for this model is based on homogeneous transformations for the evolution of an MAS under no inter-agent communication, local inter-agent communication, and intelligent perception by agents. Different communication protocols for MAS evolution, the robustness of tracking of a desired motion by an MAS evolving in n, and the effect of communication delays in an MAS evolving under consensus algorithms or homogeneous maps are also explored. Featuring appendices which introduce the requisite concepts from continuum kinematics and graph theory, this monograph will provide advanced graduate students and researchers with the necessary background to understand and apply the methods presented.

Control of Discrete-Time Descriptor Systems takes an anisotropy-based approach to the explanation of random input disturbance with an information-theoretic representation. It describes the random input signal more precisely, and the anisotropic norm minimization included in the book enables readers to tune their controllers better through the mathematical methods provided. The book contains numerous examples of practical applications of descriptor systems in various fields, from robotics to economics, and presents an information-theoretic approach to the mathematical description of coloured noise. Anisotropy-based analysis and design for descriptor systems is supplied along with proofs of basic statements, which help readers to understand the algorithms proposed, and to undertake their own numerical simulations. This book serves as a source of ideas for academic researchers and postgraduate students working in the control of discrete-time systems. The control design procedures outlined are numerically effective and easily implementable in MATLAB (R)

Robust and Fault-Tolerant Control proposes novel automatic control strategies for nonlinear systems developed by means of artificial neural networks and pays special attention to robust and fault-tolerant approaches. The book discusses robustness and fault tolerance in the context of model predictive control, fault accommodation and reconfiguration, and iterative learning control strategies. Expanding on its theoretical deliberations the monograph includes many case studies demonstrating how the proposed approaches work in practice. The most important features of the book include: a comprehensive review of neural network architectures with possible applications in system modelling and control; a concise introduction to robust and fault-tolerant control; step-by-step presentation of the control approaches proposed; an abundance of case studies illustrating the important steps in designing robust and fault-tolerant control; and a large number of figures and tables facilitating the performance analysis of the control approaches described. The material presented in this book will be useful for researchers and engineers who wish to avoid spending excessive time in searching neural-network-based control solutions. It is written for electrical, computer science and automatic control engineers interested in control theory and their applications. This monograph will also interest postgraduate students engaged in self-study of nonlinear robust and fault-tolerant control.

This book addresses a range of solutions and effective control techniques for Microbial Fuel Cells (MFCs), intended as a response to the increased energy consumption and wastewater production stemming from globalization. It describes the fundamentals of MFCs and control-oriented mathematical models, and provides detailed information on uncertain parameters. Various control techniques like robust control with LMI, adaptive backstepping control, and exact linearization control are developed for different mathematical models. In turn, the book elaborates on the basics of adaptive control, presenting several methods in detail. It also demonstrates how MFCs can be developed at the laboratory level, equipping readers to develop their own MFCs for experimental purposes. In closing, it develops a transfer function model for MFCs by combining a system identification technique and model reference adaptive control techniques. By addressing one of the most promising sources of clean and renewable energy, this book provides a viable solution for meeting the world's increasing energy demands.

This book presents a differential geometric method for designing nonlinear observers for multiple types of nonlinear systems, including single and multiple outputs, fully and partially observable systems, and regular and singular dynamical systems. It is an exposition of achievements in nonlinear observer normal forms. The book begins by discussing linear systems, introducing the concept of observability and observer design, and then explains the difficulty of those problems for nonlinear systems. After providing foundational information on the differential geometric method, the text shows how to use the method to address observer design problems. It presents methods for a variety of systems. The authors employ worked examples to illustrate the ideas presented. Observer Design for Nonlinear Dynamical Systems will be of interest to researchers, graduate students, and industrial professionals working with control of mechanical and dynamical systems.

China Satellite Navigation Conference (CSNC 2021) Proceedings presents selected research papers from CSNC 2021 held during 22nd-25th May, 2021 in Nanchang, China. These papers discuss the technologies and applications of the Global Navigation Satellite System (GNSS), and the latest progress made in the China BeiDou System (BDS) especially. They are divided into 10 topics to match the corresponding sessions in CSNC2021 which broadly covered key topics in GNSS. Readers can learn about the BDS and keep abreast of the latest advances in GNSS techniques and applications.

This book focuses on the latest applications of nonlinear approaches in engineering and addresses a range of scientific problems. Examples focus on issues in automotive technology, including automotive dynamics, control for electric and hybrid vehicles, and autodriver algorithm for autonomous vehicles. Also included are discussions on renewable energy plants, data modeling, driver-aid methods, and low-frequency vibration. Chapters are based on invited contributions from world-class experts who advance the future of engineering by discussing the development of more optimal, accurate, efficient, cost, and energy effective systems. This book is appropriate for researchers, students, and practising engineers who are interested in the applications of nonlinear approaches to solving engineering and science problems. Presents a broad range of practical topics and approaches; Explains approaches to better, safer, and cheaper systems; Emphasises automotive applications, physical meaning, and methodologies.

Interest in the area of control of systems defined by partial differential Equations has increased strongly in recent years. A major reason has been the requirement of these systems for sensible continuum mechanical modelling and optimization or control techniques which account for typical physical phenomena. Particular examples of problems on which substantial progress has been made are the control and stabilization of mechatronic structures, the control of growth of thin films and crystals, the control of Laser and semi-conductor devices, and shape optimization problems for turbomachine blades, shells, smart materials and microdiffractive optics. This volume contains original articles by world reknowned experts in the fields of optimal control of partial differential equations, shape optimization, numerical methods for partial differential equations and fluid dynamics, all of whom have contributed to the analysis and solution of many of the problems discussed. The collection provides a state-of-the-art overview of the most challenging and exciting recent developments in the field. It is geared towards postgraduate students and researchers dealing with the theoretical and practical aspects of a wide variety of high technology problems in applied mathematics, fluid control, optimal design, and computer modelling.

This standard text gives a unified treatment of passivity and L2-gain theory for nonlinear state space systems, preceded by a compact treatment of classical passivity and small-gain theorems for nonlinear input-output maps. The synthesis between passivity and L2-gain theory is provided by the theory of dissipative systems. Specifically, the small-gain and passivity theorems and their implications for nonlinear stability and stabilization are discussed from this standpoint. The connection between L2-gain and passivity via scattering is detailed. Feedback equivalence to a passive system and resulting stabilization strategies are discussed. The passivity concepts are enriched by a generalised Hamiltonian formalism, emphasising the close relations with physical modeling and control by interconnection, and leading to novel control methodologies going beyond passivity. The potential of L2-gain techniques in nonlinear control, including a theory of all-pass factorizations of nonlinear systems, and of parametrization of stabilizing controllers, is demonstrated. The nonlinear H-infinity optimal control problem is also treated and the book concludes with a geometric analysis of the solution sets of Hamilton-Jacobi inequalities and their relation with Riccati inequalities for the linearization. * L2-Gain and Passivity Techniques in Nonlinear Control (third edition) is thoroughly updated, revised, reorganized and expanded. Among the changes, readers will find: * updated and extended coverage of dissipative systems theory * substantial new material regarding converse passivity theorems and incremental/shifted passivity * coverage of recent developments on networks of passive systems with examples * a completely overhauled and succinct introduction to modeling and control of port-Hamiltonian systems, followed by an exposition of port-Hamiltonian formulation of physical network dynamics * updated treatment of all-pass factorization of nonlinear systems The book provides graduate students and researchers in systems and control with a compact presentation of a fundamental and rapidly developing area of nonlinear control theory, illustrated by a broad range of relevant examples stemming from different application areas.

This book is a collection of selected research papers presented at the International Conference on Innovations in Electrical and Electronics Engineering (ICIEEE 2019), which was organized by the Guru Nanak Institutions, Ibrahimpatnam, Hyderabad, Telangana, India, on July 26-27, 2019. The book highlights the latest developments in electrical and electronics engineering, especially in the areas of power systems, power electronics, control systems, electrical machinery, and renewable energy. The solutions discussed here will encourage and inspire researchers, industry professionals, and policymakers to put these methods into practice.

The book focuses on new theoretical results and techniques in the field of intelligent systems and control. It provides in-depth studies on a number of major topics such as Multi-Agent Systems, Complex Networks, Intelligent Robots, Complex System Theory and Swarm Behavior, Event-Triggered Control and Data-Driven Control, Robust and Adaptive Control, Big Data and Brain Science, Process Control, Intelligent Sensor and Detection Technology, Deep learning and Learning Control Guidance, Navigation and Control of Flight Vehicles and so on. Given its scope, the book will benefit all researchers, engineers, and graduate students who want to learn about cutting-edge advances in intelligent systems, intelligent control, and artificial intelligence.

This book introduces readers to numerous multiplicative inverse functional equations and their stability results in various spaces. This type of functional equation can be of use in solving many physical problems and also has significant relevance in various scientific fields of research and study. In particular, multiplicative inverse functional equations have applications in electric circuit theory, physics, and relations connecting the harmonic mean and arithmetic mean of several values. Providing a wealth of essential insights and new concepts in the field of functional equations, the book is chiefly intended for researchers, graduate schools, graduate students, and educators, and can also used for seminars in analysis covering topics of functional equations.

This monograph investigates the existence of higher order sliding mode in discrete-time systems and propounds a new concept of discrete-time higher order sliding mode. The authors propose a definition of discrete-time higher order sliding mode and a control law is designed by means of a concept for an uncertain linear-time invariant system, as well as the behavior of the closed-loop system is analyzed. Moreover, the book includes a thorough treatment of the probabilistic and non-deterministic case, i.e. stochastic discrete-time higher order sliding mode. The target audience primarily comprises research experts in control theory but the book may also be beneficial for graduate students alike.

In two parts, this book describes the evolution of mercury cadmium telluride (HgCdTe) imager structures based upon published patents and patent applications. The first part covers monolithic arrays, and the second part describes hybrid arrays. Each part has 5 chapters, with each document placed in chronological order, with the documents with the earliest priority placed first. Focus has been directed at the steps of manufacturing and structures of imagers.

There is an index at the end of the book containing the patent number, the name of the applicant and the date of publication of each cited document.

This monograph will serve as a useful summary of the patents and patent applications in the field of mercury cadmium telluride imagers.

This book explains the fundamentals of control theory for Internet of Things (IoT) systems and smart grids and its applications. It discusses the challenges imposed by large-scale systems, and describes the current and future trends and challenges in decision-making for IoT in detail, showing the ongoing industrial and academic research in the field of smart grid domain applications. It presents step-by-step design guidelines for the modeling, design, customisation and calibration of IoT systems applied to smart grids, in which the challenges increase with each system's increasing complexity. It also provides solutions and detailed examples to demonstrate how to use the techniques to overcome these challenges, as well as other problems related to decision-making for successful implementation. Further, it anaylses the features of decision-making, such as low-complexity and fault-tolerance, and uses open-source and publicly available software tools to show readers how they can design, implement and customise their own system control instantiations. This book is a valuable resource for power engineers and researchers, as it addresses the analysis and design of flexible decision-making mechanisms for smart grids. It is also of interest to students on courses related to control of large-scale systems, since it covers the use of state-of-the-art technology with examples and solutions in every chapter. And last but not least, it offers practical advice for professionals working with smart grids.

INHALT LANG: Introduction: Introductory Survey; Vector Norm. Matrix Norm. Matrix Measure; Functional Analysis, Function Norms and Control Signals.- Differential Sensitivity. Small-Scale Perturbation: Kronecker Calculus in Control Theory; Analysis Using Matrices and Control Theory; Eigenvalue and Eigenvector Differential Sensitivity; Transition Matrix Differential Sensitivity; Characteristic Polynomial Differential Sensitivity; Optimal Control and Performance Sensitivity; Desensitizing Control.- Robustness in the Time Domain: General Stability Bounds in Perturbed Systems; Robust Dynamic Interval Systems; Lyapunov-Based Methods for Perturbed Continuous-Time Systems; Lyapunov-Based Methods for Perturbed Discrete-Time Systems; Robust Pole Assignment; Models for Optimal and Interconnected Systems; Robust State Feedback Using Ellipsoid Sets; Robustness of Observers and Kalman-Bucy Filters; Initial Condition Perturbation, Overshoot and Robustness; Lnp-Stability and Robust Nonlinear Control.- Robustness in the Frequency Domain: Uncertain Polynomials. Interval Polynomials; Eigenvalues and Singular Values of Complex Matrices; Resolvent Matrix and Stability Radius; Robustness Via Singular-Value Analysis; Generalized Nyquist Stability of Perturbed Systems; Block-Structured Uncertainty and Structured Singular Value; Performance Robustness; Robust Controllers Via Spectral Radius Technique.- Coprime Factorization and Minimax Frequency Optimization: Robustness Based on the Internal Model Principle; Parametrization and Factorization of Systems; Hardy Space Robust Design.- Robustness Via Approximative Models: Robust Hyperplane Design in Variable Structure Control; SIngular Perturbaitons. Unmodelled High-Frequendy Dynamics; Control Using Aggregation Models; Optimum Control of Approximate and Nonlinear Systems; System Analysis via Orthogonal Functions; System Analysis Via Pulse Functions and Piecewise Linear Functions; Orthogonal Decomposition Applications.

This book focuses on the finite-time control of attitude stabilization, attitude tracking for individual spacecraft, and finite-time control of attitude synchronization. It discusses formation reconfiguration for multiple spacecraft in complex networks, and provides a new fast nonsingular terminal sliding mode surface (FNTSMS). Further, it presents newly designed controllers and several control laws to enhance the performance of spacecraft systems and meet related demands, such as strong disturbance rejection and high-precision control. As such, the book establishes a fundamental framework for these topics, while also highlighting the importance of integrated analysis. It is a useful resource for all researchers and students who are interested in this field, as well as engineers whose work involves designing flight vehicles.

Introduction to Control System Design equips students with the basic concepts, tools, and knowledge they need to effectively design automatic control systems. The text not only teaches readers how to design a control system, it inspires them to innovate and expand current methods to address new automation technology challenges and opportunities. The text is designed to support a two-quarter/semester course and is organized into two main parts. Part I covers basic linear system analysis and model-assembly concepts. It presents readers with a short history of control system design and introduces basic control concepts using first-order and second order-systems. Additional chapters address the modeling of mechanical and electrical systems, as well as assembling complex models using subsystem interconnection tools. Part II focuses on linear control system design. Students learn the fundamentals of feedback control systems; stability, regulation, and root locus design; time delay, plant uncertainty, and robust stability; and state feedback and linear quadratic optimization. The final chapter covers observer theory and output feedback control and reformulates the linear quadratic optimization problem as the more general H2 problem.

This thesis develops a systematic, data-based dynamic modeling framework for industrial processes in keeping with the slowness principle. Using said framework as a point of departure, it then proposes novel strategies for dealing with control monitoring and quality prediction problems in industrial production contexts. The thesis reveals the slowly varying nature of industrial production processes under feedback control, and integrates it with process data analytics to offer powerful prior knowledge that gives rise to statistical methods tailored to industrial data. It addresses several issues of immediate interest in industrial practice, including process monitoring, control performance assessment and diagnosis, monitoring system design, and product quality prediction. In particular, it proposes a holistic and pragmatic design framework for industrial monitoring systems, which delivers effective elimination of false alarms, as well as intelligent self-running by fully utilizing the information underlying the data. One of the strengths of this thesis is its integration of insights from statistics, machine learning, control theory and engineering to provide a new scheme for industrial process modeling in the era of big data.

This book investigates the performance limitation issues in networked feedback systems. The fact that networked feedback systems consist of control and communication devices and systems calls for the integration of control theory and information theory. The primary contributions of this book lie in two aspects: the newly-proposed information-theoretic measures and the newly-discovered control performance limitations. We first propose a number of information notions to facilitate the analysis. Using those notions, classes of performance limitations of networked feedback systems, as well as state estimation systems, are then investigated. In general, the book presents a unique, cohesive treatment of performance limitation issues of networked feedback systems via an information-theoretic approach. This book is believed to be the first to treat the aforementioned subjects systematically and in a unified manner, offering a unique perspective differing from existing books.

This monograph combines the commutant lifting theorem for operator theory and the state space method from system theory to provide a unified approach for solving both stationary and nonstationary interpolation problems with norm constraints. Included are the operator-valued versions of the tangential Nevanlinna-Pick problem, the Hermite-FejA(c)r problem, the Nehari problem, the Sarason problem, and the two-sided Nudelman problem, and their nonstationary analogues. The main results concern the existence of solutions, the explicit construction of the central solutions in state space form, the maximum entropy property of the central solutions, and state space parametrizations of all solutions. Direct connections between the various interpolation problems are displayed. Applications to H infinity] control problems are presented. This monograph should appeal to a wide group of mathematicians and engineers. The material is self-contained and may be used for advanced graduate courses and seminars.