This monograph is a revised version of the D.Phil. thesis of the first author, submitted in October 1990 to the University of Oxford. This work investigates the problem of mobile robot navigation using sonar. We view model-based navigation as a process of tracking naturally occurring environment features, which we refer to as "targets". Targets that have been predicted from the environment map are tracked to provide that are observed, but not predicted, vehicle position estimates. Targets represent unknown environment features or obstacles, and cause new tracks to be initiated, classified, and ultimately integrated into the map. Chapter 1 presents a brief definition of the problem and a discussion of the basic research issues involved. No attempt is made to survey ex haustively the mobile robot navigation literature-the reader is strongly encouraged to consult other sources. The recent collection edited by Cox and Wilfong [34] is an excellent starting point, as it contains many of the standard works of the field. Also, we assume familiarity with the Kalman filter. There are many well-known texts on the subject; our notation derives from Bar-Shalom and Fortmann [7]. Chapter 2 provides a detailed sonar sensor model. A good sensor model of our approach to navigation, and is used both for is a crucial component predicting expected observations and classifying unexpected observations.

From grading and preparing harvested vegetables to the tactile probing of a patient 's innermost recesses, mechatronics has become part of our way of life. This cutting-edge volume features the 30 best papers of the 13th International Conference on Mechatronics and Machine Vision in Practice. Although there is no shortage of theoretical and technical detail in these chapters, they have a common theme in that they describe work that has been applied in practice.

There has been significant interest for designing flight controllers for small-scale unmanned helicopters. Such helicopters preserve all the physical attributes of their full-scale counterparts, being at the same time more agile and dexterous. This book presents a comprehensive and well justified analysis for designing flight controllers for small-scale unmanned helicopters guarantying flight stability and tracking accuracy. The design of the flight controller is a critical and integral part for developing an autonomous helicopter platform. Helicopters are underactuated, highly nonlinear systems with significant dynamic coupling that needs to be considered and accounted for during controller design and implementation. Most reliable mathematical tools for analysis of control systems relate to modern control theory. Modern control techniques are model-based since the controller architecture depends on the dynamic representation of the system to be controlled. Therefore, the flight controller design problem is tightly connected with the helicopter modeling.

This book provides a step-by-step methodology for designing, evaluating and implementing efficient flight controllers for small-scale helicopters. Design issues that are analytically covered include:

An illustrative presentation of both linear and nonlinear models of ordinary differential equations representing the helicopter dynamics. A detailed presentation of the helicopter equations of motion is given for the derivation of both model types. In addition, an insightful presentation of the main rotor's mechanism, aerodynamics and dynamics is also provided. Both model types are of low complexity, physically meaningful and capable of encapsulating the dynamic behavior of a large class of small-scale helicopters.

An illustrative and rigorous derivation of mathematical control algorithms based on both the linear and nonlinear representation of the helicopter dynamics. Flight controller designs guarantee that the tracking objectives of the helicopter's inertial position (or velocity) and heading are achieved. Each controller is carefully constructed by considering the small-scale helicopter's physical flight capabilities. Concepts of advanced stability analysis are used to improve the efficiency and reduce the complexity of the flight control system. Controller designs are derived in both continuous time and discrete time covering discretization issues, which emerge from the implementation of the control algorithm using microprocessors.

Presentation of the most powerful, practical and efficient methods for extracting the helicopter model parameters based on input/output responses, collected by the measurement instruments. This topic is of particular importance for real-life implementation of the control algorithms.

This book is suitable for students and researches interested in the development and the mathematical derivation of flight controllers for small-scale helicopters. Background knowledge in modern control is required."

Driven by the need to achieve superior control performances for robots with hyper degrees of freedom, the virtual decomposition control approach is thoroughly presented in this book. This approach uses subsystem (such as links and joints of a complex robot) dynamics to conduct control design, while guaranteeing the stability and convergence of the entire complex robot without compromising the rigorousness of the system analysis. The central concept of this approach is the definition of the virtual stability. The stability of the entire complex robot is mathematically equivalent to the virtual stability of every subsystem. This fact allows us to convert a large problem to a few simple problems with mathematical certainty.

This book comprises fourteen chapters. The first five chapters form the foundation of this approach. The remaining nine chapters are relatively independent. Starting from Chapter 6, each chapter deals with a particular type of systems including motor/transmission assemblies, hydraulic robots, coordinated multiple robots, space robots, humanoid robots, adaptive teleoperation, and modular robot manipulators. At the end, the extensions of this approach to distributed-parameter systems and to electrical circuits are given, paving the way for other applications to follow.

This book is intended for practitioners, researchers, and graduate students who have acquired fundamental knowledge on robotics and control systems and have been committed to achieving the best control performances on complex robotics systems and beyond.

Robot algorithms are abstractions of computational processes that control or reason about motion and perception in the physical world. Because actions in the physical world are subject to physical laws and geometric constraints, the design and analysis of robot algorithms raise a unique combination of questions in control theory, computational and differential geometry, and computer science. Algorithms serve as a unifying theme in the multi-disciplinary field of robotics.

This volume consists of selected contributions to the sixth Workshop on the Algorithmic Foundations of Robotics. This is a highly competitive meeting of experts in the field of algorithmic issues related to robotics and automation.

This book is of interest to researchers inquiring about modern topics and methods in the kinematics, control and design of robotic manipulators. It considers the full range of robotic systems, including serial, parallel and cable driven manipulators, both planar and spatial. The systems range from being less than fully mobile to kinematically redundant to overconstrained. In addition to recognized areas, this book also presents recent advances in emerging areas such as the design and control of humanoids and humanoid subsystems, and the analysis, modeling and simulation of human body motions, as well as the mobility analysis of protein molecules and the development of machines which incorporate man.

The complexity and sensitivity of modern industrial processes and systems increasingly require adaptable advanced control protocols. These controllers have to be able to deal with circumstances demanding "judgement" rather than simple "yes/no," "on/off" responses, circumstances where an imprecise linguistic description is often more relevant than a cut-and-dried numerical one. The ability of fuzzy systems to handle numeric and linguistic information within a single framework renders them efficacious in this form of expert control system.

Divided into two parts, Fuzzy Logic, Identification and Predictive Control first shows you how to construct static and dynamic fuzzy models using the numerical data from a variety of real-world industrial systems and simulations. The second part demonstrates the exploitation of such models to design control systems employing techniques like data mining.

Fuzzy Logic, Identification and Predictive Control is a comprehensive introduction to the use of fuzzy methods in many different control paradigms encompassing robust, model-based, PID-like and predictive control. This combination of fuzzy control theory and industrial serviceability will make a telling contribution to your research whether in the academic or industrial sphere and also serves as a fine roundup of the fuzzy control area for the graduate student.

Advances in Industrial Control aims to report and encourage the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrialcontrol.

The problem of viability of hybrid systems is considered in this work. A model for a hybrid system is developed including a means of including three forms of uncertainty: transition dynamics, structural uncertainty, and parametric uncertainty. A computational basis for viability of hybrid systems is developed and applied to three control law classes. An approach is developed for robust viability based on two extensions of the controllability operator. The three-tank example is examined for both the viability problem and robust viability problem.

The theory is applied through simulation to an active magnetic bearing system and to a batch polymerization process showing that viability can be satisfied in practice. The problem of viable attainability is examined based on the controllability operator approach introduced by Nerode and colleagues. Lastly, properties of the controllability operator are presented.

The lectures that comprise this volume constitute a comprehensive survey of the many and various aspects of integrable dynamical systems. The present edition is a streamlined, revised and updated version of a 1997 set of notes that was published as Lecture Notes in Physics, Volume 495. This volume will be complemented by a companion book - Lecture Notes in Physics, Volume 644 - dedicated to discrete integrable systems. Both volumes address primarily graduate students and nonspecialist researchers but will also benefit lecturers looking for suitable material for advanced courses and researchers interested in specific topics.

The articles in this volume cover power system model reduction, transient and voltage stability, nonlinear control, robust stability, computation and optimization and have been written by some of the leading researchers in these areas. This book should be of interest to power and control engineers, and applied mathematicians.

Self-contained introduction to control theory that emphasizes on the most modern designs for high performance and robustness.

It assumes no previous coursework and offers three chapters of key topics summarizing classical control.

To provide readers with a deeper understanding of robust control theory than would be otherwise possible, the text incorporates mathematical derivations and proofs.

Includes many elementary examples and advanced case studies using MATLAB Toolboxes.

Nanorobots can be defined as intelligent systems with overall dimensions at or below the micrometer range that are made of assemblies of nanoscale components with individual dimensions ranging between 1 to 100 nm. These devices can now perform a wide variety of tasks at the nanoscale in a wide variety of fields including but not limited to fields such as manufacturing, medicine, supply chain, biology, and aerospace. Nanorobotics: Current Approaches and Techniques offers a comprehensive overview of this emerging interdisciplinary field with a wide ranging discussion that includes nano-manipulation and industrial nanorobotics, nanorobotic manipulation in biology and medicine, nanorobotic sensing, navigation and swarm behavior and CNT, and protein and DNA-based nanorobotics.

The idea that some day robots may have emotions has captured the imagination of many and has been dramatized by robots and androids in such famous movies as 2001: A Space Odyssey's HAL or Star Trek's Lt. Commander Data. By contrast, the editors of this book have assembled a panel of experts in neuroscience and artificial intelligence who have dared to tackle the issue of whether robots can have emotions from a purely scientific point of view. The study of the brain now usefully informs study of the social, communicative, adaptive, regulatory, and experiential aspects of emotion and offers support for the idea that we exploit our own psychological responses in order to feel others' emotions. The contributors show the many ways in which the brain can be analyzed to shed light on emotions. Fear, reward, and punishment provide structuring concepts for a number of investigations. Neurochemistry reveals the ways in which different "neuromodulators" such as serotonin, dopamine and opioids can affect the emotional balance of the brain. And studies of different regions such as the amygdala and orbitofrontal cortex provide a view of the brain as a network of interacting subsystems. Related studies in artificial intelligence and robotics are discussed and new multi-level architectures are proposed that make it possible for emotions to be implanted. It is now an accepted task in robotics to build robots that perceived human expressions of emotion and can "express" simulated emotions to ease interactions with humans. Looking towards future innovations, some scientists posit roles for emotion as a powerful self-motivational tool as well as a way to work effectively in a group. But daunting questions remain as we ask what may be the nature of emotions in future generations of robots that share neither our biological heritage nor our need to share emotions with our fellow humans. All of these issues are covered in this timely and stimulating book which is written for researchers and graduate students in neuroscience, cognitive science, psychology, robotics and artificial intelligence.

This book presents the most important findings from the 9th International Conference on Modelling, Identification and Control (ICMIC'17), held in Kunming, China on July 10-12, 2017. It covers most aspects of modelling, identification, instrumentation, signal processing and control, with a particular focus on the applications of research in multi-agent systems, robotic systems, autonomous systems, complex systems, and renewable energy systems. The book gathers thirty comprehensively reviewed and extended contributions, which help to promote evolutionary computation, artificial intelligence, computation intelligence and soft computing techniques to enhance the safety, flexibility and efficiency of engineering systems. Taken together, they offer an ideal reference guide for researchers and engineers in the fields of electrical/electronic engineering, mechanical engineering and communication engineering.

Calibration is playing an increasingly important role in industrial robotics. Higher accuracy demands are being placed on flexible assembly and manufacturing systems which in turn require robot manufacturers to produce higher quality precision robots.

Air traffic controllers need advanced information and automated systems to provide a safe environment for everyone traveling by plane. One of the primary challenges in developing training for automated systems is to determine how much a trainee will need to know about the underlying technologies to use automation safely and efficiently. To ensure safety and success, task analysis techniques should be used as the basis of the design for training in automated systems in the aviation and aerospace industries. Automated Systems in the Aviation and Aerospace Industries is a pivotal reference source that provides vital research on the application of underlying technologies used to enforce automation safety and efficiency. While highlighting topics such as expert systems, text mining, and human-machine interface, this publication explores the concept of constructing navigation algorithms, based on the use of video information and the methods of the estimation of the availability and accuracy parameters of satellite navigation. This book is ideal for aviation professionals, researchers, and managers seeking current research on information technology used to reduce the risk involved in aviation.

As robotic systems make their way into standard practice, they have opened the door to a wide spectrum of complex applications. Such applications usually demand that the robots be highly intelligent. Future robots are likely to have greater sensory capabilities, more intelligence, higher levels of manual dexter ity, and adequate mobility, compared to humans. In order to ensure high-quality control and performance in robotics, new intelligent control techniques must be developed, which are capable of coping with task complexity, multi-objective decision making, large volumes of perception data and substantial amounts of heuristic information. Hence, the pursuit of intelligent autonomous robotic systems has been a topic of much fascinating research in recent years. On the other hand, as emerging technologies, Soft Computing paradigms consisting of complementary elements of Fuzzy Logic, Neural Computing and Evolutionary Computation are viewed as the most promising methods towards intelligent robotic systems. Due to their strong learning and cognitive ability and good tolerance of uncertainty and imprecision, Soft Computing techniques have found wide application in the area of intelligent control of robotic systems."

Instrumentation and Control Systems, Third Edition, addresses the basic principles of modern instrumentation and control systems, including examples of the latest devices, techniques and applications. The book provides a comprehensive introduction on the subject, with Laplace presented in a simple and easily accessible form and complemented by an outline of the mathematics that would be required to progress to more advanced levels of study. Taking a highly practical approach, the author combines underpinning theory with numerous case studies and applications throughout, thus enabling the reader to directly apply the content to real-world engineering contexts. Coverage includes smart instrumentation, DAQ, crucial health and safety considerations, and practical issues such as noise reduction, maintenance and testing. PLCs and ladder programming is incorporated in the text, as well as new information introducing various software programs used for simulation. The overall approach of this book makes it an ideal text for all introductory level undergraduate courses in control engineering and instrumentation.

One of the fundamental requirements for the success of a robot task is the capability to handle interaction between manipulator and environment. The quantity that describes the state of interaction more effectively is the contact force at the manipulator's end effector. High values of contact force are generally undesirable since they may stress both the manipulator and the manipulated object; hence the need to seek for effective force control strategies. The book provides a theoretical and experimental treatment of robot interaction control. In the framework of model-based operational space control, stiffness control and impedance control are presented as the basic strategies for indirect force control; a key feature is the coverage of six-degree-of-freedom interaction tasks and manipulator kinematic redundancy. Then, direct force control strategies are presented which are obtained from motion control schemes suitably modified by the closure of an outer force regulation feedback loop. Finally, advanced force and position control strategies are presented which include passivity-based, adaptive and output feedback control schemes. Remarkably, all control schemes are experimentally tested on a setup consisting of a seven-joint industrial robot with open control architecture and force/torque sensor. The topic of robot force control is not treated in depth in robotics textbooks, in spite of its crucial importance for practical manipulation tasks. In the few books addressing this topic, the material is often limited to single-degree-of-freedom tasks. On the other hand, several results are available in the robotics literature but no dedicated monograph exists. The book is thus aimed at filling this gap by providing a theoretical and experimental treatment of robot force control.

This book presents technologies and solutions related to the test and launch control of rockets and other vehicles, and offers the first comprehensive and systematic introduction to the contributions of the Chinese Long March (Chang Zheng in Chinese, or abbreviated as CZ) rockets in this field. Moreover, it discusses the role of this technology in responsive, reliable, and economical access to space, which is essential for the competitiveness of rockets. The need for rapid development of the aerospace industry for both governmental and commercial projects is addressed. This book is a valuable reference resource for practitioners, and many examples and resources are included, not only from Chinese rockets but also from many other vehicles. It covers guidelines, technologies, and solutions on testing and launch control before rocket takeoff, covering equipment-level testing, system-level testing, simulation tests, etc.

Ontologically Controlled Autonomous Systems: Principles, Operations and Architecture presents the main principles, operations and architecture involved in the design of a novel type of supervisory controller called an ontological controller. An ontological controller can be used to supervise any type of controller; however its intended applications are industrial-strength complex autonomous control systems using advanced programmable controllers. An ontological controller supervises a programmable controller in order to: Detect dynamically when the programmable controller is in a problematic control situation due to a violation of ontological assumptions and thus unable to achieve a pre-specified control goal (i.e. the identification operation), and When possible, move the programmable controller into such a state from which it can regain its control and eventually achieve the pre-specified control goal in spite of the previous violation of ontological assumptions (i.e. the recovery operation). Ontologically Controlled Autonomous Systems: Principles, Operations and Architecture presents for the first time a complete formal framework and results for ontological control. All results presented in the book originate from the practical industrial experience of the author. The intended readers for Ontologically Controlled Autonomous Systems: Principles, Operations and Architecture are professionals and students working in industrial control, discrete control, discrete-event systems, artificial intelligence, autonomous systems, programmable (logic) control design, robotics, real-time planning, safety-critical systems, Petri nets and PLC standards such as IEC1131.

Based on interdisciplinary research into "Directional Change", a new data-driven approach to financial data analysis, Detecting Regime Change in Computational Finance: Data Science, Machine Learning and Algorithmic Trading applies machine learning to financial market monitoring and algorithmic trading. Directional Change is a new way of summarising price changes in the market. Instead of sampling prices at fixed intervals (such as daily closing in time series), it samples prices when the market changes direction ("zigzags"). By sampling data in a different way, this book lays out concepts which enable the extraction of information that other market participants may not be able to see. The book includes a Foreword by Richard Olsen and explores the following topics: Data science: as an alternative to time series, price movements in a market can be summarised as directional changes Machine learning for regime change detection: historical regime changes in a market can be discovered by a Hidden Markov Model Regime characterisation: normal and abnormal regimes in historical data can be characterised using indicators defined under Directional Change Market Monitoring: by using historical characteristics of normal and abnormal regimes, one can monitor the market to detect whether the market regime has changed Algorithmic trading: regime tracking information can help us to design trading algorithms It will be of great interest to researchers in computational finance, machine learning and data science. About the Authors Jun Chen received his PhD in computational finance from the Centre for Computational Finance and Economic Agents, University of Essex in 2019. Edward P K Tsang is an Emeritus Professor at the University of Essex, where he co-founded the Centre for Computational Finance and Economic Agents in 2002.

This book proposes a complete pipeline for monocular (single camera) based 3D mapping of terrestrial and underwater environments. The aim is to provide a solution to large-scale scene modeling that is both accurate and efficient. To this end, we have developed a novel Structure from Motion algorithm that increases mapping accuracy by registering camera views directly with the maps. The camera registration uses a dual approach that adapts to the type of environment being mapped. In order to further increase the accuracy of the resulting maps, a new method is presented, allowing detection of images corresponding to the same scene region (crossovers). Crossovers then used in conjunction with global alignment methods in order to highly reduce estimation errors, especially when mapping large areas. Our method is based on Visual Bag of Words paradigm (BoW), offering a more efficient and simpler solution by eliminating the training stage, generally required by state of the art BoW algorithms. Also, towards developing methods for efficient mapping of large areas (especially with costs related to map storage, transmission and rendering in mind), an online 3D model simplification algorithm is proposed. This new algorithm presents the advantage of selecting only those vertices that are geometrically representative for the scene.

Consisting of 23 refereed contributions, this volume offers a broad and diverse view of current research in control and estimation of partial differential equations. Topics addressed include, but are not limited to - control and stability of hyperbolic systems related to elasticity, linear and nonlinear; - control and identification of nonlinear parabolic systems; - exact and approximate controllability, and observability; - Pontryagin's maximum principle and dynamic programming in PDE; and - numerics pertinent to optimal and suboptimal control problems. This volume is primarily geared toward control theorists seeking information on the latest developments in their area of expertise. It may also serve as a stimulating reader to any researcher who wants to gain an impression of activities at the forefront of a vigorously expanding area in applied mathematics.