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Nonlinear Industrial Control Systems presents a range of mostly optimisation-based methods for severely nonlinear systems; it discusses feedforward and feedback control and tracking control systems design. The plant models and design algorithms are provided in a MATLAB® toolbox that enable both academic examples and industrial application studies to be repeated and evaluated, taking into account practical application and implementation problems. The text makes nonlinear control theory accessible to readers having only a background in linear systems, and concentrates on real applications of nonlinear control. It covers: different ways of modelling nonlinear systems including state space, polynomial-based, linear parameter varying, state-dependent and hybrid; design techniques for nonlinear optimal control including generalised-minimum-variance, model predictive control, quadratic-Gaussian, factorised and H∞ design methods; design philosophies that are suitable for aerospace, automotive, marine, process-control, energy systems, robotics, servo systems and manufacturing; steps in design procedures that are illustrated in design studies to define cost-functions and cope with problems such as disturbance rejection, uncertainties and integral wind-up; and baseline non-optimal control techniques such as nonlinear Smith predictors, feedback linearization, sliding mode control and nonlinear PID. Nonlinear Industrial Control Systems is valuable to engineers in industry dealing with actual nonlinear systems. It provides students with a comprehensive range of techniques and examples for solving real nonlinear control design problems.
This book analyses recent advances in non-linear state estimation and application of such estimation schemes to industrial systems control. This book is mainly addressed to graduate students, researchers and engineers working on the problems of estimation and control of non-linear dynamical systems. This book comes to address the increasing interest of the engineering community in control systems that process and integrate information coming from various types of sensors. By providing analysis on non-trivial problems of joint estimation and control for non-linear dynamical systems, according to recently developed filtering methods and non-linear control techniques, this book is a useful reference for researchers and engineers.
This monograph addresses problems of: • nonlinear control, estimation and filtering for robotic manipulators (multi-degree-of freedom rigid-link robots, flexible-link robots, underactuated, redundant and cooperating manipulators and closed-chain robotic mechanisms); and• nonlinear control, estimation and filtering for autonomous robotic vehicles operating on the ground, in the air, and on and under water, independently and in cooperating groups. The book is a thorough treatment of the entire range of applications of robotic manipulators and autonomous vehicles. The nonlinear control and estimation methods it develops can be used generically, being suitable for a wide range of robotic systems. Such methods can improve robustness, precision and fault-tolerance in robotic manipulators and vehicles at the same time as enabling the reliable functioning of these systems under variable conditions, model uncertainty and external perturbations.
Mechatronics represents a unifying interdisciplinary and intelligent engineering science paradigm that features an interdisciplinary knowledge area and interactions in terms of the ways of work and thinking, practical experiences, and theoretical knowledge. Mechatronics successfully fuses (but is not limited to) mechanics, electrical, electronics, informatics and intelligent systems, intelligent control systems and advanced modeling, intelligent and autonomous robotic systems, optics, smart materials, actuators and biomedical and biomechanics, energy and sustainable development, systems engineering, artificial intelligence, intelligent computer control, computational intelligence, precision engineering and virtual modeling into a unified framework that enhances the design of products and manufacturing processes. Interdisciplinary Mechatronics concerns mastering a multitude of disciplines, technologies, and their interaction, whereas the science of mechatronics concerns the invention and development of new theories, models, concepts and tools in response to new needs evolving from interacting scientific disciplines. The book includes two sections, the first section includes chapters introducing research advances in mechatronics engineering, and the second section includes chapters that reflects the teaching approaches (theoretical, projects, and laboratories) and curriculum development for under- and postgraduate studies. Mechatronics engineering education focuses on producing engineers who can work in a high-technology environment, emphasize real-world hands-on experience, and engage in challenging problems and complex tasks with initiative, innovation and enthusiasm. Contents: 1. Interdisciplinary Mechatronics Engineering Science and the Evolution of Human Friendly and Adaptive Mechatronics, Maki K. Habib. 2. Micro-Nanomechatronics for Biological Cell Analysis and Assembly, Toshio Fukuda, Masahiro Nakajima, Masaru Takeuchi, Tao Yue and Hirotaka Tajima. 3. Biologically Inspired CPG-Based Locomotion Control System of a Biped Robot Using Nonlinear Oscillators with Phase Resetting, Shinya Aoi. 4. Modeling a Human’s Learning Processes toward Continuous Learning Support System, Tomohiro Yamaguchi, Kouki Takemori and Keiki Takadama. 5. PWM Waveform Generation Using Pulse-Type Hardware Neural Networks, Ken Saito, Minami Takato, Yoshifumi Sekine and Fumio Uchikoba. 6. Parallel Wrists: Limb Types, Singularities and New Perspectives, Raffaele Di Gregorio. 7. A Robot-Assisted Rehabilitation System – RehabRoby, Duygun Erol Barkana and Fatih Özkul. 8. MIMO Actuator Force Control of a Parallel Robot for Ankle Rehabilitation, Andrew Mcdaid, Yun Ho Tsoi and Shengquan Xie. 9. Performance Evaluation of a Probe Climber for Maintaining Wire Rope, Akihisa Tabata, Emiko Hara and Yoshio Aoki. 10. Fundamentals on the Use of Shape Memory Alloys in Soft Robotics, Matteo Cianchetti. 11. Tuned Modified Transpose Jacobian Control of Robotic Systems, S. A. A. Moosavian and M. Karimi. 12. Derivative-Free Nonlinear Kalman Filtering for PMSG Sensorless Control, Gerasimos Rigatos, Pierluigi Siano and Nikolaos Zervos. 13. Construction and Control of Parallel Robots, Moharam Habibnejad Korayem, Soleiman Manteghi and Hami Tourajizadeh. 14. A Localization System for Mobile Robot Using Scanning Laser and Ultrasonic Measurement, Kai Liu, Hongbo Li and Zengqi Sun. 15. Building of Open-Structure Wheel-Based Mobile Robotic Platform, Aleksandar Rodic and Ivan Stojkovic. 16. Design and Physical Implementation of Holonomous Mobile Robot–Holbos, Jasmin Velagic, Admir Kaknjo, Faruk Dautovic, Muhidin Hujdur and Nedim Osmic. 17. Advanced Artificial Vision and Mobile Devices for New Applications in Learning, Entertainment and Cultural Heritage Domains, Gian Luca Foresti, Niki Martinel, Christian Micheloni and Marco Vernier. 18. Application of Stereo Vision and ARM Processor for Motion Control, Moharam Habibnejad Korayem, Michal Irani and Saeed Rafee Nekoo. 19. Mechatronics as Science and Engineering – or Both, Balan Pillai and Vesa Salminen. 20. A Mechatronic Platform for Robotic Educational Activities, Ioannis Kostavelis, Evangelos Boukas, Lazaros Nalpantidis and Antonios Gasteratos. 21. The Importance of Practical Activities in the Formation of Mechatronic Engineers, Joao Carlos M. Carvalho and Vera Lúcia D.S. Franco About the Authors Maki K. Habib is Professor of Robotics and Mechatronics in the School of Science and Engineering, at the American University in Cairo, Egypt. He has been regional editor (Africa/Middle East,) for the International Journal of Mechatronics and Manufacturing Systems (IJMMS) since 2010. He is the recipient of academic awards and has published many articles and books. J. Paulo Davim is Aggregate Professor in the Department of Mechanical Engineering at the University of Aveiro, Portugal and is Head of MACTRIB (Machining and Tribology Research Group). His main research interests include manufacturing, materials and mechanical engineering.
Focused on renewable energy systems and the development of information and communication technologies (ICTs) for their integration in smart grids, this book presents recent advances and methods that help to ensure that power generation from renewable sources remains stable, that power losses are minimized, and that the reliable functioning of these power generation units is maintained. The book highlights key topics and technologies for renewable energy systems including the intelligent control of power generators, power electronics that connect renewable power generation units to the grid, and fault diagnosis for power generators and power electronics. In particular, the following topics are addressed: • Modeling and control of power generators (PMSGs, DFIGs); • Modeling and control of power electronics (converters, inverters); • Modeling and fault diagnosis of the transmission and distribution Grid; and • Modelling and control of distributed power generation units (interconnected synchronous generators or photovoltaic units). Because of the above coverage, members of the wider engineering community will find that the nonlinear control and estimation methods presented provide essential insights into the functioning of renewable energy power systems, while the academic community will find the book a valuable textbook for undergraduate or graduate courses on renewable energy systems.
This book gives readers in-depth know-how on methods of state estimation for nonlinear control systems. It starts with an introduction to dynamic control systems and system states and a brief description of the Kalman filter. In the following chapters, various state estimation techniques for nonlinear systems are discussed, including the extended, unscented and cubature Kalman filters. The cubature Kalman filter and its variants are introduced in particular detail because of their efficiency and their ability to deal with systems with Gaussian and/or non-Gaussian noise. The book also discusses information-filter and square-root-filtering algorithms, useful for state estimation in some real-time control system design problems. A number of case studies are included in the book to illustrate the application of various nonlinear filtering algorithms. Nonlinear Filtering is written for academic and industrial researchers, engineers and research students who are interested in nonlinear control systems analysis and design. The chief features of the book include: dedicated coverage of recently developed nonlinear, Jacobian-free, filtering algorithms; examples illustrating the use of nonlinear filtering algorithms in real-world applications; detailed derivation and complete algorithms for nonlinear filtering methods, which help readers to a fundamental understanding and easier coding of those algorithms; and MATLAB® codes associated with case-study applications, which can be downloaded from the Springer Extra Materials website.
Incorporating intelligence in industrial systems can help to increase productivity, cut-off production costs, and to improve working conditions and safety in industrial environments. This need has resulted in the rapid development of modeling and control methods for industrial systems and robots, of fault detection and isolation methods for the prevention of critical situations in industrial work-cells and production plants, of optimization methods aiming at a more profitable functioning of industrial installations and robotic devices and of machine intelligence methods aiming at reducing human intervention in industrial systems operation. To this end, the book analyzes and extends some main directions of research in modeling and control for industrial systems. These are: (i) industrial robots, (ii) mobile robots and autonomous vehicles, (iii) adaptive and robust control of electromechanical systems, (iv) filtering and stochastic estimation for multisensor fusion and sensorless control of industrial systems (iv) fault detection and isolation in robotic and industrial systems, (v) optimization in industrial automation and robotic systems design, and (vi) machine intelligence for robots autonomy. The book will be a useful companion to engineers and researchers since it covers a wide spectrum of problems in the area of industrial systems. Moreover, the book is addressed to undergraduate and post-graduate students, as an upper-level course supplement of automatic control and robotics courses.
This monograph presents recent advances in differential flatness theory and analyzes its use for nonlinear control and estimation. It shows how differential flatness theory can provide solutions to complicated control problems, such as those appearing in highly nonlinear multivariable systems and distributed-parameter systems. Furthermore, it shows that differential flatness theory makes it possible to perform filtering and state estimation for a wide class of nonlinear dynamical systems and provides several descriptive test cases. The book focuses on the design of nonlinear adaptive controllers and nonlinear filters, using exact linearization based on differential flatness theory. The adaptive controllers obtained can be applied to a wide class of nonlinear systems with unknown dynamics, and assure reliable functioning of the control loop under uncertainty and varying operating conditions. The filters obtained outperform other nonlinear filters in terms of accuracy of estimation and computation speed. The book presents a series of application examples to confirm the efficiency of the proposed nonlinear filtering and adaptive control schemes for various electromechanical systems. These include: · industrial robots; · mobile robots and autonomous vehicles; · electric power generation; · electric motors and actuators; · power electronics; · internal combustion engines; · distributed-parameter systems; and · communication systems. Differential Flatness Approaches to Nonlinear Control and Filtering will be a useful reference for academic researchers studying advanced problems in nonlinear control and nonlinear dynamics, and for engineers working on control applications in electromechanical systems.