"There are three words that characterize this work: thoroughness, completeness and clarity. The authors are congratulated for taking the time to write an excellent linear systems textbook! a ]The authors have used their mastery of the subject to produce a textbook that very effectively presents the theory of linear systems as it has evolved over the last thirty years. The result is a comprehensive, complete and clear exposition that serves as an excellent foundation for more advanced topics in system theory and control." a "IEEE Transactions on Automatic Control

"In assessing the present book as a potential textbook for our first graduate linear systems course, I find...[that] Antsaklis and Michel have contributed an expertly written and high quality textbook to the field and are to be congratulateda ]. Because of its mathematical sophistication and completeness the present book is highly recommended for use, both as a textbook as well as a reference." a "Automatica

Linear systems theory plays a broad and fundamental role in electrical, mechanical, chemical and aerospace engineering, communications, and signal processing. A thorough introduction to systems theory with emphasis on control is presented in this self-contained textbook.

The book examines the fundamental properties that govern the behavior of systems by developing their mathematical descriptions. Linear time-invariant, time-varying, continuous-time, and discrete-time systems are covered. Rigorous development of classic and contemporary topics in linear systems, as well as extensive coverage of stability and polynomial matrix/fractional representation, provide the necessary foundation for further study of systemsand control.

Linear Systems is written as a textbook for a challenging one-semester graduate course; a solutions manual is available to instructors upon adoption of the text. The booka (TM)s flexible coverage and self-contained presentation also make it an excellent reference guide or self-study manual.

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For a treatment of linear systems that focuses primarily on the time-invariant case using streamlined presentation of the material with less formal and more intuitive proofs, see the authorsa (TM) companion book entitled A Linear Systems Primer.

In Interconnect-centric Design for Advanced SoC and NoC, we have tried to create a comprehensive understanding about on-chip interconnect characteristics, design methodologies, layered views on different abstraction levels and finally about applying the interconnect-centric design in system-on-chip design.
Traditionally, on-chip communication design has been done using rather ad-hoc and informal approaches that fail to meet some of the challenges posed by next-generation SOC designs, such as performance and throughput, power and energy, reliability, predictability, synchronization, and management of concurrency. To address these challenges, it is critical to take a global view of the communication problem, and decompose it along lines that make it more tractable. We believe that a layered approach similar to that defined by the communication networks community should also be used for on-chip communication design.
The design issues are handled on physical and circuit layer, logic and architecture layer, and from system design methodology and tools point of view. Formal communication modeling and refinement is used to bridge the communication layers, and network-centric modeling of multiprocessor on-chip networks and socket-based design will serve the development of platforms for SoC and NoC integration. Interconnect-centric Design for Advanced SoC and NoC is concluded by two application examples: interconnect and memory organization in SoCs for advanced set-top boxes and TV, and a case study in NoC platform design for more generic applications.

The research book is a continuation of the authors' previous works, which are focused on recent advances in computer vision methodologies and technical solutions using conventional and intelligent paradigms. The book gathers selected contributions addressing aerial and satellite image processing and related fields. Topics covered include novel tensor and wave models, a new comparative morphology scheme, warping compensation in video stabilization, image deblurring based on physical processes of blur impacts, and a rapid and robust core structural verification algorithm for feature extraction in images and videos, among others. All chapters focus on practical implementations. Given the tremendous interest among researchers in the development and applications of computer vision paradigms in the field of business, engineering, medicine, security and aviation, this book offers a timely guide.

Hybrid Computational Intelligent Systems – Modeling, Simulation and Optimization unearths the latest advances in evolving hybrid intelligent modeling and simulation of human-centric data-intensive applications optimized for real-time use, thereby enabling researchers to come up with novel breakthroughs in this ever-growing field. Salient features include the fundamentals of modeling and simulation with recourse to knowledge-based simulation, interaction paradigms, and human factors, along with the enhancement of the existing state of art in a high-performance computing setup. In addition, this book presents optimization strategies to evolve robust and failsafe intelligent system modeling and simulation. The volume also highlights novel applications for different engineering problems including signal and data processing, speech, image, sensor data processing, innovative intelligent systems, and swarm intelligent manufacturing systems. Features: A self-contained approach to integrating the principles of hybrid computational ntelligence with system modeling and simulation Well-versed foundation of computational intelligence and its application to real life engineering problems Elucidates essential background, concepts, definitions, and theories thereby putting forward a complete treatment on the subject Effective modeling of hybrid intelligent systems forms the backbone of almost every operative system in real-life Proper simulation of real-time hybrid intelligent systems is a prerequisite for deriving any real-life system solution Optimized system modeling and simulation enable real-time and failsafe operations of the existing hybrid intelligent system solutions Information presented in an accessible way for researchers, engineers, developers, and practitioners from academia and industry working in all major areas and interdisciplinary areas of hybrid computational intelligence and communication systems to evolve human-centered modeling and simulations of real-time data-intensive intelligent systems.

The presence of considerable time delays in the dynamics of many industrial processes, leading to difficult problems in the associated closed-loop control systems, is a well-recognized phenomenon. The performance achievable in conventional feedback control systems can be significantly degraded if an industrial process has a relatively large time delay compared with the dominant time constant. Under these circumstances, advanced predictive control is necessary to improve the performance of the control system significantly.The book is a focused treatment of the subject matter, including the fundamentals and some state-of-the-art developments in the field of predictive control. Three main schemes for advanced predictive control are addressed in this book:- Smith Predictive Control;- Generalised Predictive Control;- a form of predictive control based on Finite Spectrum Assignment.A substantial part of the book addresses application issues in predictive control, providing several interesting case studies for more application-oriented readers. Thus, while the book is written to serve as an advanced control reference on predictive control for researchers, postgraduates and senior undergraduates, it should be equally useful to those industrial practitioners who are keen to explore the use of advanced predictive control in real problems. The prerequisite for gaining maximum benefit from this book is a basic knowledge of control systems, such as that imparted by a first undergraduate course on control systems engineering.

A comprehensive treatment of model-based fuzzy control systems

This volume offers full coverage of the systematic framework for the stability and design of nonlinear fuzzy control systems. Building on the Takagi-Sugeno fuzzy model, authors Tanaka and Wang address a number of important issues in fuzzy control systems, including stability analysis, systematic design procedures, incorporation of performance specifications, numerical implementations, and practical applications.

Issues that have not been fully treated in existing texts, such as stability analysis, systematic design, and performance analysis, are crucial to the validity and applicability of fuzzy control methodology. Fuzzy Control Systems Design and Analysis addresses these issues in the framework of parallel distributed compensation, a controller structure devised in accordance with the fuzzy model.

This balanced treatment features an overview of fuzzy control, modeling, and stability analysis, as well as a section on the use of linear matrix inequalities (LMI) as an approach to fuzzy design and control. It also covers advanced topics in model-based fuzzy control systems, including modeling and control of chaotic systems. Later sections offer practical examples in the form of detailed theoretical and experimental studies of fuzzy control in robotic systems and a discussion of future directions in the field.

Fuzzy Control Systems Design and Analysis offers an advanced treatment of fuzzy control that makes a useful reference for researchers and a reliable text for advanced graduate students in the field.

In the last two decades fractional differential equations have been used more frequently in physics, signal processing, fluid mechanics, viscoelasticity, mathematical biology, electro chemistry and many others. It opens a new and more realistic way to capture memory dependent phenomena and irregularities inside the systems by using more sophisticated mathematical analysis.

This monograph is based on the authors work on stabilization and control design for continuous and discrete fractional order systems. The initial two chapters and some parts of the third chapter are written in tutorial fashion, presenting all the basic concepts of fractional order system and a brief overview of sliding mode control of fractional order systems. The other parts contain deal with robust finite time stability of fractional order systems, integral sliding mode control of fractional order systems, co-operative control of multi-agent systems modeled as fractional differential equation, robust stabilization of discrete fractional order systems, high performance control using soft variable structure control and contraction analysis by integer and fractional order infinitesimal variations."

In this book, modeling and control design of electric motors, namely step motors, brushless DC motors and induction motors, are considered. The book focuses on recent advances on feedback control designs for various types of electric motors, with a slight emphasis on stepper motors. For this purpose, the authors explore modeling of these devices to the extent needed to provide a high-performance controller, but at the same time one amenable to model-based nonlinear designs. The control designs focus primarily on recent robust adaptive nonlinear controllers to attain high performance. It is shown that the adaptive robust nonlinear controller on its own achieves reasonably good performance without requiring the exact knowledge of motor parameters. While carefully tuned classical controllers often achieve required performance in many applications, it is hoped that the advocated robust and adaptive designs will lead to standard universal controllers with minimal need for fine tuning of control parameters.

Computer vision-based crack-like object detection has many useful applications, such as pavement surface inspection, underground pipeline inspection, bridge cracking monitoring, railway track assessment, etc. However, in most contexts, cracks appear as thin, irregular long-narrow objects, and often are buried into complex, textured background with high diversity which make the crack detection very challenging. During the past a few years, the deep learning technique has achieved great success and has been utilized for solving a variety of object detection problems. However, using deep learning for accurate crack localization is non-trivial. This book discusses crack-like object detection problem in a comprehensive way. It starts by discussing traditional image processing approaches for solving this problem, and then introduces deep learning-based methods. The book provides a comprehensive review of object detection problems and focuses on the most challenging problem, crack-like object detection, to dig deep into the deep learning method. It includes examples of real-world problems, which are easy to understand and could be a good tutorial for introducing computer vision and machine learning.

This book presents a wide range of techniques that lead to novel strategies for effecting intelligent control of complex systems that are typically characterised by uncertainty, nonlinear dynamics, component failure, unpredictable disturbances, multi-modality and high dimensional spaces. The underlying design philosophy is based on effecting closed-loop control in the presence of plant or environmental uncertainty and complexity by utilizing various types of neural network architectures, ranging from multilayer perceptron to radical basis function and modular network models. The uncertainty and complexity are typified by unknown nonlinear functionals, and temporal or spatial multi-modality. Deterministic and stochastic conditions, as well as continuous and discrete time dynamics are taken into consideration. The presented designs are firmly rooted in the techniques of adaptive control, reconfigurable control, multiple model control, stochastic adaptive control, lyapunov stability theory and neural networks. The techniques are shown to enhance the performance of the control system in the presence of the higher levels of complexity and uncertainty associated with modern plants, which demand superior intelligence and autonomy from the controller. The presented designs are supported both by theory and by numerous results from simulation experiments. The book also includes extensive reviews on general aspects concerning the fields of intelligent, nonlinear and stochastic control.

The book is concerned with contemporary methodologies used for automatic text summarization. It proposes interesting approaches to solve well-known problems on text-summarization using computational intelligence (CI) techniques including cognitive approaches. A better understanding of the cognitive basis of the summarization task is still an open research issue, an extent of its use in text summarization is highlighted for further exploration. With the ever-growing text and people on research has little time to spare for extensive reading, where, summarized information helps for a better understanding of the context at a shorter time. This book helps students and researchers to automatically summarize the text documents in an efficient and effective way. The computational approaches and the research techniques presented guides to achieve text summarization at ease. The summarized text generated supports readers to learn the context or the domain at a quicker pace. The book is presented with reasonable amount of illustrations and examples convenient for the readers to understand and implement for their use. The book is not to make readers understand what text summarization is, but for people to perform text summarization using various approaches. This also describes measures that can help to evaluate, determine and explore the best possibilities for text summarization to analyse and use for any specific purpose. The illustration is based on social media and healthcare domain, which shows the possibilities to work with any domain for summarization. The new approach for text summarization based on cognitive intelligence is presented for further exploration in the field.

The series Advances in Industrial Control aims to report and encourage technology transfer in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computer methods, new applications, new philosophies. . . , new challenges. Much of this development work resides in industrial reports, feasibility study papers and the reports of advanced collaborative projects. The series offers an opportunity for researchers to present an extended exposition of such new work in all aspects of industrial control for widerand rapid dissemination. Benchmarking is a technique first applied by Rank Xerox in the late 1970s for business processes. As a subject in the commercial arena, benchmarking thrives with, for example, a European Benchmarking Forum. It has taken rather longer for benchmarking to make the transfer to the technical domain and even now the subject is making a slow headway. Akey research step in this direction was taken by Harris (1989) who used minimum variance control as a benchmark for controller loop assessment. This contribution opened up the area and a significant specialist literature has now developed. Significant support for the methodologywas given by Honeywell who have controller assessment routines in their process control applications software; therefore, it is timely to welcome a (first) monograph on controller performance assessment by Biao Huang and Sirish Shah to the Advances in Industrial Control series.

Flexible mechanical systems experience undesirable vibration in response to environmental and operational forces. The very existence of vibrations can limit the accuracy of sensitive instruments or cause significant errors in applications where high-precision positioning is essential so in many situations control of vibrations is a necessity.

Piezoelectric transducers have been used in countless applications as sensors, actuators, or both. When traditional passive vibration control techniques fail to meet requirements, piezoelectric transducers in conjunction with feedback controllers can be used effectively to suppress vibrations.

Piezoelectric Transducers for Vibration Control and Damping presents recent developments in vibration control systems that employ embedded piezoelectric sensors and actuators. In particular, it covers various ways in which active vibration control systems can be designed for piezoelectric laminated structures, paying distinct attention to how such control systems can be implemented in real time. The text contains numerous examples and experimental results obtained from laboratory-scale apparatus, with details of how similar setups can be built.

Features and topics:

• An overview of piezoelectricity.
• Modelling of flexible structures with embedded piezoelectric sensors and actuators.
• Feedback control of structural vibration using PPF and resonant controllers.
• A comprehensive treatment of piezoelectric shunt damping systems using systems-theoretic tools.
• A paradigm for designing active high-performance piezoelectric shunts.
• Innovative techniques to deal with the problem of hysteresis inpiezoelectric transducers.
• Instrumentation for piezoelectric sensors and actuators.
• Applications in atomic force and scanning tunneling microscopy.

An essential text and reference for graduates, researchers, and professionals working in mechanical engineering, aerospace engineering and mechatronics disciplines, this book will be a specially useful resource for scientists and engineers engaged in vibration control research.

This application-oriented monograph focuses on a novel and complex type of control systems. Written on an engineering level, including fundamentals, advanced methods and applications, the book applies techniques originating from new methods such as artificial intelligence, fuzzy logic, neural networks etc.

This book deals with the analysis, the design and the implementation of the mechatronic systems. Classical and modern tools are developed for the analysis and the design for such systems. Robust control, H-Infinity and guaranteed cost control theory are also used for analysis and design of mechatronic systems. Different controller such as state feedback, static output feedback and dynamic output feedback controllers are used to stabilize mechatronic systems.

Heuristic algorithms are provided to solve the design of the classical controller such as PID, phase lead, phase lag and phase lead-lag controllers while linear matrix inequalities (LMI) algorithms are provided for finding solutions to the state feedback, static output feedback and dynamic output feedback controllers.

The theory presented in the different chapters of the volume is applied to numerical examples to show the usefulness of the theoretical results. Some case studies are also provided to show how the developed concepts apply for real system.

Emphasis is also put on the implementation in real-time for some real systems that we have developed in our mechatronic laboratory and all the detail is provided to give an idea to the reader how to implement its own mechatronic system.

Mechatronics Systems: Analysis, Design and Implementation is an excellent textbook for undergraduate and graduate students in mechatronic system and control theory and as a reference for academic researchers in control or mathematics with interest in control theory. The reader should have completed first-year graduate courses in control theory, linear algebra, and linear systems. It will also be of great value to engineers practising in fields where the systems can be modeled by linear time invariant systems.

Markov decision process (MDP) models are widely used for modeling sequential decision-making problems that arise in engineering, economics, computer science, and the social sciences. Many real-world problems modeled by MDPs have huge state and/or action spaces, giving an opening to the curse of dimensionality and so making practical solution of the resulting models intractable. In other cases, the system of interest is too complex to allow explicit specification of some of the MDP model parameters, but simulation samples are readily available (e.g., for random transitions and costs). For these settings, various sampling and population-based algorithms have been developed to overcome the difficulties of computing an optimal solution in terms of a policy and/or value function. Specific approaches include adaptive sampling, evolutionary policy iteration, evolutionary random policy search, and model reference adaptive search.
This substantially enlarged new edition reflects the latest developments in novel algorithms and their underpinning theories, and presents an updated account of the topics that have emerged since the publication of the first edition. Includes:
innovative material on MDPs, both in constrained settings and with uncertain transition properties;
game-theoretic method for solving MDPs;
theories for developing roll-out based algorithms; and
details of approximation stochastic annealing, a population-based on-line simulation-based algorithm.
The self-contained approach of this book will appeal not only to researchers in MDPs, stochastic modeling, and control, and simulation but will be a valuable source of tuition and reference for students of control and operations research.

Drives and Control for Industrial Automation presents the material necessary for an understanding of servo control in automation. Beginning with a macroscopic view of its subject, treating drives and control as parts of a single system, the book then pursues a detailed discussion of the major components of servo control: sensors, controllers and actuators. Throughout, the mechatronic approach a synergistic integration of the components is maintained, in keeping with contemporary practice.

The authors holistic approach does not preclude the reader from learning in a step-by-step fashion each chapter contains material that can be studied separately without compromising understanding. Drives are described in several chapters organized according to the way they are usually classified in industry, each comprised of its actuators and sensors. The controller is discussed alongside. Topics of recent and current interest piezoelectricity, digital communications and future trends are detailed in their own dedicated chapters.

Drives and Control for Industrial Automation is primarily written for engineers and researchers interested in the applications of sensors, actuators and control systems in the automated environment. The discussion is thorough with the basics laid out succinctly but in sufficient detail to be useful to non-expert readers so students will also find this monograph a profitable source of information."

The DARPA Grand Challenge was a landmark in the field of robotics: a race by autonomous vehicles through 132 miles of rough Nevada terrain. It showcased exciting and unprecedented capabilities in robotic perception, navigation, and control. The event took place in October 2005 and drew teams of competitors from academia and industry, as well as many garage hobbyists. This book presents fifteen technical papers that describe each team's driverless vehicle, race strategy, and insights. As a whole, they present the state of the art in autonomous vehicle technology and offer a glimpse of future technology for tomorrow 's driverless cars.

This book presents a class of novel optimal control methods and games schemes based on adaptive dynamic programming techniques. For systems with one control input, the ADP-based optimal control is designed for different objectives, while for systems with multi-players, the optimal control inputs are proposed based on games. In order to verify the effectiveness of the proposed methods, the book analyzes the properties of the adaptive dynamic programming methods, including convergence of the iterative value functions and the stability of the system under the iterative control laws. Further, to substantiate the mathematical analysis, it presents various application examples, which provide reference to real-world practices.

Extremum-seeking control tracks a varying maximum or minimum in a performance function such as output or cost. It attempts to determine the optimal performance of a control system as it operates, thereby reducing downtime and the need for system analysis. Extremum-seeking Control and Applications is divided into two parts. In the first, the authors review existing analog-optimization-based extremum-seeking control including gradient-, perturbation- and sliding-mode-based control designs. They then propose a novel numerical-optimization-based extremum-seeking control based on optimization algorithms and state regulation. This control design is developed for simple linear time-invariant systems and then extended for a class of feedback linearizable nonlinear systems. The two main optimization algorithms - line search and trust region methods - are analyzed for robustness. Finite-time and asymptotic state regulators are put forward for linear and nonlinear systems respectively. Further design flexibility is achieved using the robustness results of the optimization algorithms and the asymptotic state regulator by which existing nonlinear adaptive control techniques can be introduced for robust design. The approach used is easier to implement and tends to be more robust than those that use perturbation-based extremum-seeking control. The second part of the book deals with a variety of applications of extremum-seeking control: a comparative study of extremum-seeking control schemes in antilock braking system design; source seeking, formation control, collision and obstacle avoidance for groups of autonomous agents; mobile radar networks; and impedance matching. MATLAB (R)/Simulink (R) code which can be downloaded from www.springer.com/ISBN helps readers to reproduce the results presented in the text and gives them a head start for implementing the algorithms in their own applications. Extremum-seeking Control and Applications will interest academics and graduate students working in control, and industrial practitioners from a variety of backgrounds: systems, automotive, aerospace, communications, semiconductor and chemical engineering.

Intelligent control is a rapidly developing, complex and challenging field with great practical importance and potential. Because of the rapidly developing and interdisciplinary nature of the subject, there are only a few edited volumes consisting of research papers on intelligent control systems but little is known and published about the fundamentals and the general know-how in designing, implementing and operating intelligent control systems.

Intelligent control system emerged from artificial intelligence and computer controlled systems as an interdisciplinary field. Therefore the book summarizes the fundamentals of knowledge representation, reasoning, expert systems and real-time control systems and then discusses the design, implementation verification and operation of real-time expert systems using G2 as an example. Special tools and techniques applied in intelligent control are also described including qualitative modelling, Petri nets and fuzzy controllers. The material is illlustrated with simple examples taken from the field of intelligent process control.

Online fault diagnosis is crucial to ensure safe operation of complex dynamic systems in spite of faults affecting the system behaviors. Consequences of the occurrence of faults can be severe and result in human casualties, environmentally harmful emissions, high repair costs, and economical losses caused by unexpected stops in production lines. The majority of real systems are hybrid dynamic systems (HDS). In HDS, the dynamical behaviors evolve continuously with time according to the discrete mode (configuration) in which the system is. Consequently, fault diagnosis approaches must take into account both discrete and continuous dynamics as well as the interactions between them in order to perform correct fault diagnosis. This book presents recent and advanced approaches and techniques that address the complex problem of fault diagnosis of hybrid dynamic and complex systems using different model-based and data-driven approaches in different application domains (inductor motors, chemical process formed by tanks, reactors and valves, ignition engine, sewer networks, mobile robots, planetary rover prototype etc.). These approaches cover the different aspects of performing single/multiple online/offline parametric/discrete abrupt/tear and wear fault diagnosis in incremental/non-incremental manner, using different modeling tools (hybrid automata, hybrid Petri nets, hybrid bond graphs, extended Kalman filter etc.) for different classes of hybrid dynamic and complex systems.

A set of original results in the ?eld of high-level design of logical control devices and systems is presented in this book. These concern different aspects of such important and long-term design problems, including the following, which seem to be the main ones. First, the behavior of a device under design must be described properly, and some adequate formal language should be chosen for that. Second, effective algorithmsshouldbeusedforcheckingtheprepareddescriptionforcorrectness, foritssyntacticandsemanticveri?cationattheinitialbehaviorlevel.Third, the problem of logic circuit implementation must be solved using some concrete technological base; ef?cient methods of logic synthesis, test, and veri?cation should be developed for that. Fourth, the task of the communication between the control device and controlled objects (and maybe between different control devices)waitsforitssolution.Alltheseproblemsarehardenoughandcannotbe successfully solved without ef?cient methods and algorithms oriented toward computer implementation. Some of these are described in this book. The languages used for behavior description have been descended usually from two well-known abstract models which became classic: Petri nets and ?nite state machines (FSMs). Anyhow, more detailed versions are developed and described in the book, which enable to give more complete information concerningspeci?cqualitiesoftheregardedsystems.Forexample, themodelof parallelautomatonispresented, whichunliketheconventional?niteautomaton can be placed simultaneously into several places, calledpartial. As a base for circuit implementation of control algorithms, FPGA is accepted in majority of cas

The time delays in controllers and actuators can either deteriorate or improve the dynamic performance of a controlled mechanical system. Thus, it is desirable to gain an insight into the effect of time delays on the dynamics of a practical system in its design phase. This monograph represents the recent advances in system modeling, analysis of stability, robust stability and bifurcation by using some new mathematical tools such as generalized Sturm criterion and Dixon's resultant elimination of polynomials. The theoretical results are demonstrated through a number of examples of active vehicle chassis, structure control, as well as the control of chaos of mechanical systems.

Modern computer-based control systems are able to collect a large amount of information, display it to operators and store it in databases but the interpretation of the data and the subsequent decision making relies mainly on operators with little computer support. This book introduces developments in automatic analysis and interpretation of process-operational data both in real-time and over the operational history, and describes new concepts and methodologies for developing intelligent, state space-based systems for process monitoring, control and diagnosis. The book brings together new methods and algorithms from process monitoring and control, data mining and knowledge discovery, artificial intelligence, pattern recognition, and causal relationship discovery, as well as signal processing. It also provides a framework for integrating plant operators and supervisors into the design of process monitoring and control systems.