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.

The book presents the modeling and control of hydrogen-air PEM fuel cells, including simultaneous estimation of the parameters and states, fuzzy cluster modeling, SPM-based predictive control and advanced fuzzy control. MATLAB/Simulink-based modeling and control programs are discussed in detail. With simulations and experiments, it is an essential reference for both scientists and industrial engineers.

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."

Robotics is a modern interdisciplinary field that has emerged from the marriage of computerized numerical control and remote manipulation. Today's robotic systems have intelligence features, and are able to perform dexterous and intelligent human-like actions through appropriate combination of learning, perception, planning, decision making and control. This book presents advanced concepts, techniques and applications reflecting the experience of a wide group of specialists in the field. Topics include: kinematics, dynamics, path planning and tracking, control, mobile robotics, navigation, robot programming, and sophisticated applications in the manufacturing, medical, and other areas.

This thesis proposes an effective methodology for enhancing the perceptual capabilities and achieving interaction control of the iCub humanoid robot. The method is based on the integration of measurements from different sensors (force/torque, inertial and tactile sensors) distributed along the robot's kinematic chain. Humanoid robots require a substantial amount of sensor information to create their own representations of the surrounding environment. Tactile perception is of primary importance for the exploration process. Also in humans, the tactile system is completely functional at birth. In humanoid robotics, the measurements of forces and torques that the robot exchanges with its surroundings are essential for safe interaction with the environment and with humans. The approach proposed in this thesis can successfully enhance the perceptual capabilities of robots by exploiting only a limited number of both localized and distributed sensors, providing a feasible and convenient solution for achieving active compliance control of humanoid robots.

Predictive Intelligence in Biomedical and Health Informatics focuses on imaging, computer-aided diagnosis and therapy as well as intelligent biomedical image processing and analysis. It develops computational models, methods and tools for biomedical engineering related to computer-aided diagnostics (CAD), computer-aided surgery (CAS), computational anatomy and bioinformatics. Large volumes of complex data are often a key feature of biomedical and engineering problems and computational intelligence helps to address such problems. Practical and validated solutions to hard biomedical and engineering problems can be developed by the applications of neural networks, support vector machines, reservoir computing, evolutionary optimization, biosignal processing, pattern recognition methods and other techniques to address complex problems of the real world.

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.

Parallel robots are closed-loop mechanisms presenting very good performances in terms of accuracy, velocity, rigidity and ability to manipulate large loads. They have been used in a large number of applications ranging from astronomy to flight simulators and are becoming increasingly popular in the field of machine-tool industry. This book presents a complete synthesis of the latest results on the possible mechanical architectures, analysis and synthesis of this type of mechanism. It is intended to be used by students (with over 150 exercises and numerous internet addresses), researchers (with over 650 references and anonymous ftp access to the code of some algorithms presented in this book) and engineers (for which practical results, mistakes to avoid, and applications are presented). Since the publication of the first edition (2000) there has been an impressive increase in terms of study and use of this kind of structure that are reported in this book. This second edition has been completely overhauled. The initial chapter on kinematics has been split into Inverse Kinematics and Direct Kinematics. A new chapter on calibration was added. The other chapters have also been rewritten to a large extent. The reference section has been updated to include around 45% new works that appeared after the first edition.

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.

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.

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.

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."

Especially designed as self-sustaining oscillating systems, resonant robotic systems use the natural modes of oscillation of electromechanical modules for their movements. In fact, manipulator systems built on these principles demonstrate record-breaking characteristics in performance. The authors summarize the results and experience of research on, and development of, resonant robotic systems. For the readers convenience, a presentation of design concepts is followed by solutions to new dynamical and control problems. The book is intended for designers, researchers and graduate students.

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.

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.

Distributed robotics is a rapidly growing, interdisciplinary research area lying at the intersection of computer science, communication and control systems, and electrical and mechanical engineering. The goal of the Symposium on Distributed Autonomous Robotic Systems (DARS) is to exchange and stimulate research ideas to realize advanced distributed robotic systems.

This volume of proceedings includes 43 original contributions presented at the Tenth International Symposium on Distributed Autonomous Robotic Systems (DARS 2010), which was held in November 2010 at the Ecole Polytechnique Federale de Lausanne (EPFL), Switzerland. The selected papers in this volume are authored by leading researchers from Asia, Europa, and the Americas, thereby providing a broad coverage and perspective of the state-of-the-art technologies, algorithms, system architectures, and applications in distributed robotic systems. The book is organized into four parts, each representing one critical and long-term research thrust in the multi-robot community: distributed sensing (Part I); localization, navigation, and formations (Part II); coordination algorithms and formal methods (Part III); modularity, distributed manipulation, and platforms (Part IV). "

This monograph provides comprehensive guidelines on the current and future trends of innovative simulation systems. In particular, their important components, such as augmented reality and unmanned vehicles are presented. The book consists of three parts. Each part presents good practices, new methods, concepts of systems and new algorithms. Presented challenges and solutions are the results of research and conducted by the contributing authors. The book describes and evaluates the current state of knowledge in the field of innovative simulation systems. Throughout the chapters there are presented current issues and concepts of systems, technology, equipment, tools, research challenges and current, past and future applications of simulation systems. The book is addressed to a wide audience: academic staff, representatives of research institutions, employees of companies and government agencies as well as students and graduates of technical universities in the country and abroad. The book can be a valuable source of information for constructors and developers of innovative simulation systems and their components. Scientists and researchers involved in mechanics, control algorithms, image processing, computer vision or data fusion can find many valuable suggestions and solutions.

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.

As the use and relevance of robotics for countless scientific purposes grows all the time, research into the many diverse elements of the subject becomes ever more important and in demand. This volume examines in depth the most topical, complex issues of modelling and identification in robotics. The book is divided into three main parts. The !first part is devoted to robot dynamics modelling and identification of robot and load parameters, incorporating friction torques, discussing identification schemes, and presenting simulations and experiment al results of robot and load dynamic parameters identification. A general concept of robot programming language for research and educational purposes is examined and there is a detailed outline of its basic structures along with hardware requirements, which both constitute an open robot controller architecture. Finally a hybrid controller is derived, and several experimental results of this system are outlined. This impressive discussion of the topic covers both the theoretical and practical, illustrated throughout by examples and experimental results, and will be of value to anyone researching or practising within the field of robotics, automation and system i dentification or to control engineers.

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.

Experimental Robotics XV is the collection of papers presented at the International Symposium on Experimental Robotics, Roppongi, Tokyo, Japan on October 3-6, 2016. 73 scientific papers were selected and presented after peer review. The papers span a broad range of sub-fields in robotics including aerial robots, mobile robots, actuation, grasping, manipulation, planning and control and human-robot interaction, but shared cutting-edge approaches and paradigms to experimental robotics. The readers will find a breadth of new directions of experimental robotics. The International Symposium on Experimental Robotics is a series of bi-annual symposia sponsored by the International Foundation of Robotics Research, whose goal is to provide a forum dedicated to experimental robotics research. Robotics has been widening its scientific scope, deepening its methodologies and expanding its applications. However, the significance of experiments remains and will remain at the center of the discipline. The ISER gatherings are a venue where scientists can gather and talk about robotics based on this central tenet.

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.