This thesis introduces a new integrated algorithm for the detection of lane-level irregular driving. To date, there has been very little improvement in the ability to detect lane level irregular driving styles, mainly due to a lack of high performance positioning techniques and suitable driving pattern recognition algorithms. The algorithm combines data from the Global Positioning System (GPS), Inertial Measurement Unit (IMU) and lane information using advanced filtering methods. The vehicle state within a lane is estimated using a Particle Filter (PF) and an Extended Kalman Filter (EKF). The state information is then used within a novel Fuzzy Inference System (FIS) based algorithm to detect different types of irregular driving. Simulation and field trial results are used to demonstrate the accuracy and reliability of the proposed irregular driving detection method.

The problem of controlling or stabilizing a system of differential equa tions in the presence of random disturbances is intuitively appealing and has been a motivating force behind a wide variety of results grouped loosely together under the heading of "Stochastic Control." This book is concerned with a special instance of this general problem, the "Adaptive LQ Regulator," which is a stochastic control problem of partially observed type that can, in certain cases, be solved explicitly. We first describe this problem, as it is the focal point for the entire book, and then describe the contents of the book. The problem revolves around an uncertain linear system x(O) = x~ in R", where 0 E {1, ... , N} is a random variable representing this uncertainty and (Ai' B , C) and xJ are the coefficient matrices and initial state, respectively, of j j a linear control system, for eachj = 1, ... , N. A common assumption is that the mechanism causing this uncertainty is additive noise, and that conse quently the "controller" has access only to the observation process y( . ) where y = Cex +~.

Well-written, practice-oriented textbook, and compact textbook

Presents the contemporary state of the art of control theory and its applications

Introduces traditional problems that are useful in the automatic control of technical processes, plus

presents current issues of control

Explains methods can be easily applied for the determination of the decision algorithms in computer control and management systems

A common sense of time among all the elements of a distributed measurement and control system allows the use of new techniques for the solution of problems with complex synchronization requirements or arising from the interaction of many sensors and actuators. Such a common sense of time may be accomplished using IEEE Standard for a Precision Clock Synchronization Protocol for Networked Measurement and Control Systems (IEEE 1588-2002) to synchronize real-time clocks incorporated within each component of the system.

IEEE 1588, published in November 2002, is a technology new to the engineering community expanding the performance capabilities of Ethernet networks so that they become relevant for measurement and control; this monograph embodies the first unified treatment of the associated technology, standards and applications. Readers unfamiliar with IEEE 1588 will gain understanding of the context of the technology it represents and, from three chapters of case studies, its role in a variety of application settings.

To engineers implementing synchronization within their systems Measurement, Control, and Communication Using IEEE 1588 provides detailed discussion of the complex features of the standard. Together with the essential material on best practice and critical implementation issues, these provide invaluable assistance in the design of new applications.

The International Symposia on Distributed Autonomous Robotic Systems (DARS) started at Riken, Japan in 1992. Since then, the DARS symposia have been held every two years: in 1994 and 1996 in Japan (Riken, Wako), in 1998 in Germany (Karlsruhe), in 2000 in the USA (Knoxville, TN), in 2002 in Japan (Fukuoka), in 2004 in France (Toulouse), and in 2006 in the USA (Minneapolis, MN). The 9th DARS symposium, which was held during November 17-19 in T- kuba, Japan, hosted 84 participants from 13 countries. The 48 papers presented there were selected through rigorous peer review with a 50% acceptance ratio. Along with three invited talks, they addressed the spreading research fields of DARS, which are classifiable along two streams: theoretical and standard studies of DARS, and interdisciplinary studies using DARS concepts. The former stream includes multi-robot cooperation (task assignment methodology among multiple robots, multi-robot localization, etc.), swarm intelligence, and modular robots. The latter includes distributed sensing, mobiligence, ambient intelligence, and mul- agent systems interaction with human beings. This book not only offers readers the latest research results related to DARS from theoretical studies to application-oriented ones; it also describes the present trends of this field. With the diversity and depth revealed herein, we expect that DARS technologies will flourish soon.

"Proceedings of the First Symposium on Aviation Maintenance and Management "collects selected papers from the conference of ISAMM 2013 in China held in Xi'an on November 25-28, 2013. The book presents state-of-the-art studies on the aviation maintenance, test, fault diagnosis, and prognosis for the aircraft electronic and electrical systems. The selected works can help promote the development of the maintenance and test technology for the aircraft complex systems. Researchers and engineers in the fields of electrical engineering and aerospace engineering can benefit from the book.

Jinsong Wang is a professor at School of Mechanical and Electronic Engineering of Northwestern Polytechnical University, China.

This thesis introduces novel and significant results regarding the analysis and synthesis of positive systems, especially under l1 and L1 performance. It describes stability analysis, controller synthesis, and bounding positivity-preserving observer and filtering design for a variety of both discrete and continuous positive systems. It subsequently derives computationally efficient solutions based on linear programming in terms of matrix inequalities, as well as a number of analytical solutions obtained for special cases. The thesis applies a range of novel approaches and fundamental techniques to the further study of positive systems, thus contributing significantly to the theory of positive systems, a "hot topic" in the field of control.

This monograph studies the design of robust, monotonically-convergent iterative learning controllers for discrete-time systems. It presents a unified analysis and design framework that enables designers to consider both robustness and monotonic convergence for typical uncertainty models, including parametric interval uncertainties, iteration-domain frequency uncertainty, and iteration-domain stochastic uncertainty. The book shows how to use robust iterative learning control in the face of model uncertainty.

Stabilization, Optimal and Robust Control develops robust control of infinite-dimensional dynamical systems derived from time-dependent coupled PDEs associated with boundary-value problems. Rigorous analysis takes into account nonlinear system dynamics, evolutionary and coupled PDE behaviour and the selection of function spaces in terms of solvability and model quality.

Mathematical foundations are provided so that the book remains accessible to the non-control-specialist. Following chapters giving a general view of convex analysis and optimization and robust and optimal control, problems arising in fluid mechanical, biological and materials scientific systems are laid out in detail.

The combination of mathematical fundamentals with application of current interest will make this book of much interest to researchers and graduate students looking at complex problems in mathematics, physics and biology as well as to control theorists.

This monograph presents a wider spectrum of researches, developments, and case specific studies in the area of smart power systems and integration of renewable energy systems. The book will be for the benefit of a wider audience including researchers, postgraduate students, practicing engineers, academics, and regulatory policy makers. It covers a wide range of topics from fundamentals, and modelling and simulation aspects of traditional and smart power systems to grid integration of renewables; Micro Grids; challenges in planning and operation of a smart power system; risks, security, and stability in smart operation of a power system; and applied research in energy storage.

The idea of optimization runs through most parts of control theory. The simplest optimal controls are preplanned (programmed) ones. The problem of constructing optimal preplanned controls has been extensively worked out in literature (see, e. g., the Pontrjagin maximum principle giving necessary conditions of preplanned control optimality). However, the concept of op timality itself has a restrictive character: it is limited by what one means under optimality in each separate case. The internal contradictoriness of the preplanned control optimality ("the better is the enemy of the good") yields that the practical significance of optimal preplanned controls proves to be not great: such controls are usually sensitive to unregistered disturbances (includ ing the round-off errors which are inevitable when computer devices are used for forming controls), as there is the effect of disturbance accumulation in the control process which makes controls to be of little use on large time inter vals. This gap is mainly provoked by oversimplified settings of optimization problems. The outstanding result of control theory established in the end of the first half of our century is that controls in feedback form ensure the weak sensitivity of closed loop systems with respect to "small" unregistered internal and external disturbances acting in them (here we do not need to discuss performance indexes, since the considered phenomenon is of general nature). But by far not all optimal preplanned controls can be represented in a feedback form."

This textbook aims to provide a clear understanding of the various tools of analysis and design for robust stability and performance of uncertain dynamic systems. In model-based control design and analysis, mathematical models can never completely represent the "real world" system that is being modeled, and thus it is imperative to incorporate and accommodate a level of uncertainty into the models. This book directly addresses these issues from a deterministic uncertainty viewpoint and focuses on the interval parameter characterization of uncertain systems. Various tools of analysis and design are presented in a consolidated manner. This volume fills a current gap in published works by explicitly addressing the subject of control of dynamic systems from linear state space framework, namely using a time-domain, matrix-theory based approach. This book also: Presents and formulates the robustness problem in a linear state space model framework. Illustrates various systems level methodologies with examples and applications drawn from aerospace, electrical and mechanical engineering. Provides connections between lyapunov-based matrix approach and the transfer function based polynomial approaches. Robust Control of Uncertain Dynamic Systems: A Linear State Space Approach is an ideal book for first year graduate students taking a course in robust control in aerospace, mechanical, or electrical engineering.

This book deals with the class of singular systems with random abrupt changes also known as singular Markovian jump systems. Various problems and their robustness are tackled. The book examines both the theoretical and practical aspects of the control problems from the angle of the structural properties of linear systems. It can be used as a textbook as well as a reference for researchers in control or mathematics with interest in control theory.

This book presents research on informational and mathematical aspects of networked sensing systems. It brings together internationally reputed researchers from different communities, focused on the common theme of distributed sensing, inferencing, and control over networks. The timeliness of the book is evidenced by the explosion of several independent special sessions devoted to specific aspects of sensor networks in reputed international conferences.

This monograph presents design methodologies for (robust) fractional control systems. It shows the reader how to take advantage of the superior flexibility of fractional control systems compared with integer-order systems in achieving more challenging control requirements. There is a high degree of current interest in fractional systems and fractional control arising from both academia and industry and readers from both milieux are catered to in the text. Different design approaches having in common a trade-off between robustness and performance of the control system are considered explicitly. The text generalizes methodologies, techniques and theoretical results that have been successfully applied in classical (integer) control to the fractional case. The first part of Advances in Robust Fractional Control is the more industrially oriented. It focuses on the design of fractional controllers for integer processes. In particular, it considers fractional-order proportional-integral-derivative controllers, because integer-order PID regulators are, undoubtedly, the controllers most frequently adopted in industry. The second part of the book deals with a more general approach to fractional control systems, extending techniques (such as H-infinity optimal control and optimal input-output inversion based control) originally devised for classical integer-order control. Advances in Robust Fractional Control will be a useful reference for the large number of academic researchers in fractional control, for their industrial counterparts and for graduate students who want to learn more about this subject.

This book presents the latest results on predictive control of networked systems, where communication constraints (e.g., network-induced delays and packet dropouts) and cyber attacks (e.g., deception attacks and denial-of-service attacks) are considered. For the former, it proposes several networked predictive control (NPC) methods based on input-output models and state-space models respectively. For the latter, it designs secure NPC schemes from the perspectives of information security and real-time control. Furthermore, it uses practical experiments to demonstrate the effectiveness and applicability of all the methods, bridging the gap between control theory and practical applications. The book is of interest to academic researchers, R&D engineers, and graduate students in control engineering, networked control systems and cyber-physical systems.

The research book is focused on the recent advances in computer vision methodologies and innovations in practice. The Contributions include: * Human Action Recognition: Contour-Based and Silhouette-based Approaches. * The Application of Machine Learning Techniques to Real Time Audience Analysis System. * Panorama Construction from Multi-view Cameras in Outdoor Scenes. * A New Real-Time Method of Contextual Image Description and Its Application in Robot Navigation and Intelligent Control. * Perception of Audio Visual Information for Mobile Robot Motion Control Systems. * Adaptive Surveillance Algorithms Based on the Situation Analysis. * Enhanced, Synthetic and Combined Vision Technologies for Civil Aviation. * Navigation of Autonomous Underwater Vehicles Using Acoustic and Visual Data Processing. * Efficient Denoising Algorithms for Intelligent Recognition Systems. * Image Segmentation Based on Two-dimensional Markov Chains. The book is directed to the PhD students, professors, researchers and software developers working in the areas of digital video processing and computer vision technologies.

This book collects the latest theoretical and technological concepts in the design and control of various linear machines and drive systems. Discussing advances in the new linear machine topologies, integrated modeling, multi-objective optimization techniques, and high-performance control strategies, it focuses on emerging applications of linear machines in transportation and energy systems. The book presents both theoretical and practical/experimental results, providing a consistent compilation of fundamental theories, a compendium of current research and development activities as well as new directions to overcome critical limitations.

A mobile agent is a software program with the capability to suspend its execution and resume it on another computer. Agents are a relatively recent development in computer science, which have become a popular and useful methodology for the modelling and implementation of distributed systems, particularly those consisting of a number of largely autonomous components. The extensive use of multi-agent systems in various areas including information management, industrial control and manufacturing systems, suggests that the multi-agent systems methodology may also be appropriate for the design of power system automation systems.

IP Network-based Multi-agent Systems for Industrial Automation: Information Management, Condition Monitoring and Control of Power Systems is the first book to present an introduction to the use of the Internet protocol suite and multi-agent systems for the information management, online monitoring and control of distributed power system substations. It proposes an open architecture for information management and control, based on the concepts of multi-agent systems and mobile agents. In this book, mobile agents are applied to the retrieval and analysis of substation data, and to remote operator intervention. This book also describes a prototype implementation of the architecture, in the form of a substation information management system, which has been demonstrated and evaluated using a substation simulator. The architecture is also evaluated theoretically with respect to its performance, modifiability, functionality and reliability.

As mobile agent technologies are in the early stages the real applications of these technologies are rare; IPNetwork-based Multi-agent Systems for Industrial Automation: Information Management, Condition Monitoring and Control of Power Systems will be an excellent reference for postgraduates, researchers and academics in engineering and computer science, as well as engineers in system automation and managers in distributed industrial systems.

This book reports on the latest findings in the application of the wide area measurement systems (WAMS) in the analysis and control of power systems. The book collects new research ideas and achievements including a delay-dependent robust design method, a wide area robust coordination strategy, a hybrid assessment and choice method for wide area signals, a free-weighting matrices method and its application, as well as the online identification methods for low-frequency oscillations. The main original research results of this book are a comprehensive summary of the authors' latest six-year study. The book will be of interest to academic researchers, R&D engineers and graduate students in power systems who wish to learn the core principles, methods, algorithms, and applications of the WAMS.

The interest in control of nonlinear partial differential equation (PDE) sys tems has been triggered by the need to achieve tight distributed control of transport-reaction processes that exhibit highly nonlinear behavior and strong spatial variations. Drawing from recent advances in dynamics of PDE systems and nonlinear control theory, control of nonlinear PDEs has evolved into a very active research area of systems and control. This book the first of its kind- presents general methods for the synthesis of nonlinear and robust feedback controllers for broad classes of nonlinear PDE sys tems and illustrates their applications to transport-reaction processes of industrial interest. Specifically, our attention focuses on quasi-linear hyperbolic and parabolic PDE systems for which the manipulated inputs and measured and controlled outputs are distributed in space and bounded. We use geometric and Lyapunov-based control techniques to synthesize nonlinear and robust controllers that use a finite number of measurement sensors and control actuators to achieve stabilization of the closed-loop system, output track ing, and attenuation of the effect of model uncertainty. The controllers are successfully applied to numerous convection-reaction and diffusion-reaction processes, including a rapid thermal chemical vapor deposition reactor and a Czochralski crystal growth process. The book includes comparisons of the proposed nonlinear and robust control methods with other approaches and discussions of practical implementation issues."

This volume presents various aspects of non-integer order systems, also known as fractional systems, which have recently attracted an increasing attention in the scientific community of systems science, applied mathematics, control theory. Non-integer systems have become relevant for many fields of science and technology exemplified by the modeling of signal transmission, electric noise, dielectric polarization, heat transfer, electrochemical reactions, thermal processes, acoustics, etc. The content is divided into six parts, every of which considers one of the currently relevant problems. In the first part the Realization problem is discussed, with a special focus on positive systems. The second part considers stability of certain classes of non-integer order systems with and without delays. The third part is focused on such important aspects as controllability, observability and optimization especially in discrete time. The fourth part is focused on distributed systems where non-integer calculus leads to new and interesting results. The next part considers problems of solutions and approximations of non-integer order equations and systems. The final and most extensive part is devoted to applications. Problems from mechatronics, biomedical engineering, robotics and others are all analyzed and solved with tools from fractional systems. This volume came to fruition thanks to high level of talks and interesting discussions at RRNR 2013 - 5th Conference on Non-integer Order Calculus and its Applications that took place at AGH University of Science and Technology in Krakow, Poland, which was organized by the Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering.

This book is devoted to a novel conceptual theoretical framework of neuro science and is an attempt to show that we can postulate a very small number of assumptions and utilize their heuristics to explain a very large spectrum of brain phenomena. The major assumption made in this book is that inborn and acquired neural automatisms are generated according to the same func tional principles. Accordingly, the principles that have been revealed experi mentally to govern inborn motor automatisms, such as locomotion and scratching, are used to elucidate the nature of acquired or learned automat isms. This approach allowed me to apply the language of control theory to describe functions of biological neural networks. You, the reader, can judge the logic of the conclusions regarding brain phenomena that the book derives from these assumptions. If you find the argument flawless, one can call it common sense and consider that to be the best praise for a chain of logical conclusions. For the sake of clarity, I have attempted to make this monograph as readable as possible. Special attention has been given to describing some of the concepts of optimal control theory in such a way that it will be under standable to a biologist or physician. I have also included plenty of illustra tive examples and references designed to demonstrate the appropriateness and applicability of these conceptual theoretical notions for the neurosciences."

This book provides a comprehensive treatment of the principles underlying optimal constrained control and estimation. The contents progress from optimisation theory, fixed-horizon discrete optimal control, receding-horizon implementations and stability conditions to explicit solutions and numerical algorithms, moving horizon estimation, and connections between constrained estimation and control. Several case studies and further developments illustrate and expand the core principles.

Specific topics covered include:

a [ An overview of optimisation theory.

a [ Links to optimal control theory, including the discrete-minimum principle.

a [ Linear and nonlinear receding-horizon constrained control including stability.

a [ Constrained control solutions having a finite parameterisation for specific classes of problems.

a [ Numerical procedures for solving constrained optimisation problems.

a [ Output feedback optimal constrained control.

a [ Constrained state estimation.

a [ Duality between constrained estimation and control.

a [ Applications to finite alphabet control and estimation problems, cross-directional control, rudder-roll stabilisation of ships, and control over communication networks.

Constrained Control and Estimation is a self-contained treatment assuming that the reader has a basic background in systems theory, including linear control, stability and state-space methods. It is suitable for use in senior-level courses and as material for reference and self-study. A companion website is continually updated by the authors.

This self-contained book, written by leading experts, offers a cutting-edge, in-depth overview of the filtering and control of wireless networked systems. It addresses the energy constraint and filter/controller gain variation problems, and presents both the centralized and the distributed solutions. The first two chapters provide an introduction to networked control systems and basic information on system analysis. Chapters (3-6) then discuss the centralized filtering of wireless networked systems, presenting different approaches to deal with energy efficiency and filter/controller gain variation problems. The next part (chapters 7-10) explores the distributed filtering of wireless networked systems, addressing the main problems of energy constraint and filter gain variation. The final part (chapters 11-14) focuses on the distributed control of wireless networked systems. In view of the rapid deployment and development of wireless networked systems for communication and control applications, the book represents a timely contribution and provides valuable insights, useful methods and effective algorithms for the analysis and design of wireless networked control systems. It is a valuable resource for researchers in the control and communication communities