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An original, systematic-solution approach to uncertain nonlinear systems control and modeling using fuzzy equations and fuzzy differential equations There are various numerical and analytical approaches to the modeling and control of uncertain nonlinear systems. Fuzzy logic theory is an increasingly popular method used to solve inconvenience problems in nonlinear modeling. Modeling and Control of Uncertain Nonlinear Systems with Fuzzy Equations and Z-Number presents a structured approach to the control and modeling of uncertain nonlinear systems in industry using fuzzy equations and fuzzy differential equations. The first major work to explore methods based on neural networks and Bernstein neural networks, this innovative volume provides a framework for control and modeling of uncertain nonlinear systems with applications to industry. Readers learn how to use fuzzy techniques to solve scientific and engineering problems and understand intelligent control design and applications. The text assembles the results of four years of research on control of uncertain nonlinear systems with dual fuzzy equations, fuzzy modeling for uncertain nonlinear systems with fuzzy equations, the numerical solution of fuzzy equations with Z-numbers, and the numerical solution of fuzzy differential equations with Z-numbers. Using clear and accessible language to explain concepts and principles applicable to real-world scenarios, this book: Presents the modeling and control of uncertain nonlinear systems with fuzzy equations and fuzzy differential equations Includes an overview of uncertain nonlinear systems for non-specialists Teaches readers to use simulation, modeling and verification skills valuable for scientific research and engineering systems development Reinforces comprehension with illustrations, tables, examples, and simulations Modeling and Control of Uncertain Nonlinear Systems with Fuzzy Equations and Z-Number is suitable as a textbook for advanced students, academic and industrial researchers, and practitioners in fields of systems engineering, learning control systems, neural networks, computational intelligence, and fuzzy logic control.
An original, systematic-solution approach to uncertain nonlinear systems control and modeling using fuzzy equations and fuzzy differential equations There are various numerical and analytical approaches to the modeling and control of uncertain nonlinear systems. Fuzzy logic theory is an increasingly popular method used to solve inconvenience problems in nonlinear modeling. Modeling and Control of Uncertain Nonlinear Systems with Fuzzy Equations and Z-Number presents a structured approach to the control and modeling of uncertain nonlinear systems in industry using fuzzy equations and fuzzy differential equations. The first major work to explore methods based on neural networks and Bernstein neural networks, this innovative volume provides a framework for control and modeling of uncertain nonlinear systems with applications to industry. Readers learn how to use fuzzy techniques to solve scientific and engineering problems and understand intelligent control design and applications. The text assembles the results of four years of research on control of uncertain nonlinear systems with dual fuzzy equations, fuzzy modeling for uncertain nonlinear systems with fuzzy equations, the numerical solution of fuzzy equations with Z-numbers, and the numerical solution of fuzzy differential equations with Z-numbers. Using clear and accessible language to explain concepts and principles applicable to real-world scenarios, this book: Presents the modeling and control of uncertain nonlinear systems with fuzzy equations and fuzzy differential equations Includes an overview of uncertain nonlinear systems for non-specialists Teaches readers to use simulation, modeling and verification skills valuable for scientific research and engineering systems development Reinforces comprehension with illustrations, tables, examples, and simulations Modeling and Control of Uncertain Nonlinear Systems with Fuzzy Equations and Z-Number is suitable as a textbook for advanced students, academic and industrial researchers, and practitioners in fields of systems engineering, learning control systems, neural networks, computational intelligence, and fuzzy logic control.
This book introduces novel methods for leak and blockage detection in pipelines. The leak happens as a result of ageing pipelines or extreme pressure forced by operational error or valve rapid variation. Many factors influence blockage formation in pipes like wax deposition that leads to the formation and eventual growth of solid layers and deposition of suspended solid particles in the fluids. In this book, initially, different categories of leak detection are overviewed. Afterwards, the observability and controllability of pipeline systems are analysed. Control variables can be usually presented by pressure and flow rates at the start and end points of the pipe. Different cases are considered based on the selection of control variables to model the system. Several theorems are presented to test the observability and controllability of the system. In this book, the leakage flow in the pipelines is studied numerically to find the relationship between leakage flow and pressure difference. Removing leakage completely is almost impossible; hence, the development of a formal systematic leakage control policy is the most reliable approach to reducing leakage rates.
This book highlights the latest research in computational intelligence and its applications. It covers both conventional and trending approaches in individual chapters on Fuzzy Systems, Intelligence in Robotics, Deep Learning Approaches, Optimization and Classification, Detection, Inference and Prediction, Hybrid Methods, Emerging Intelligence, Intelligent Health Care, and Engineering Data- and Model-Driven Applications. All chapters are based on peer-reviewed contributions presented at the 19th Annual UK Workshop on Computational Intelligence, held in Portsmouth, UK, on 4–6 September 2019. The book offers a valuable reference guide for readers with expertise in computational intelligence or who are seeking a comprehensive and timely review of the latest trends in computational intelligence. Special emphasis is placed on novel methods and their use in a wide range of application areas, updating both academics and professionals on the state of the art.
This volume gathers the latest advances, innovations, and applications in the field of robotics engineering, as presented by leading international researchers and engineers at the Latin American Symposium on Industrial and Robotic Systems (LASIRS), held in Tampico, Mexico on October-November 30-01 2019. The contributions cover all major areas of R&D and innovation in simulation, optimization, and control of robotics, such as design and optimization of robots using numerical and metaheuristic methods, autonomous and control systems, industrial compliance solutions, numerical simulations for manipulators and robots, metaheuristics applied to robotics problems, Industry 4.0, control and automation in petrochemical processes, simulation and control in aerospace and aeronautics, and education in robotics. The conference represented a unique platform to share the latest research and developments in simulation, control and optimization of robotic systems, and to promote cooperation among specialists in machine and mechanism area.
This book focuses on the core areas of computing and their applications in the real world. Presenting papers from the Computing Conference 2020 covers a diverse range of research areas, describing various detailed techniques that have been developed and implemented. The Computing Conference 2020, which provided a venue for academic and industry practitioners to share new ideas and development experiences, attracted a total of 514 submissions from pioneering academic researchers, scientists, industrial engineers and students from around the globe. Following a double-blind, peer-review process, 160 papers (including 15 poster papers) were selected to be included in these proceedings. Featuring state-of-the-art intelligent methods and techniques for solving real-world problems, the book is a valuable resource and will inspire further research and technological improvements in this important area.
A comprehensive exploration of the control schemes of human-robot interactions In Human-Robot Interaction Control Using Reinforcement Learning, an expert team of authors delivers a concise overview of human-robot interaction control schemes and insightful presentations of novel, model-free and reinforcement learning controllers. The book begins with a brief introduction to state-of-the-art human-robot interaction control and reinforcement learning before moving on to describe the typical environment model. The authors also describe some of the most famous identification techniques for parameter estimation. Human-Robot Interaction Control Using Reinforcement Learning offers rigorous mathematical treatments and demonstrations that facilitate the understanding of control schemes and algorithms. It also describes stability and convergence analysis of human-robot interaction control and reinforcement learning based control. The authors also discuss advanced and cutting-edge topics, like inverse and velocity kinematics solutions, H2 neural control, and likely upcoming developments in the field of robotics. Readers will also enjoy: A thorough introduction to model-based human-robot interaction control Comprehensive explorations of model-free human-robot interaction control and human-in-the-loop control using Euler angles Practical discussions of reinforcement learning for robot position and force control, as well as continuous time reinforcement learning for robot force control In-depth examinations of robot control in worst-case uncertainty using reinforcement learning and the control of redundant robots using multi-agent reinforcement learning Perfect for senior undergraduate and graduate students, academic researchers, and industrial practitioners studying and working in the fields of robotics, learning control systems, neural networks, and computational intelligence, Human-Robot Interaction Control Using Reinforcement Learning is also an indispensable resource for students and professionals studying reinforcement learning.
Presents strategies with reachability graph analysis for optimizing resource allocation systems Supervisory Control and Scheduling of Resource Allocation Systems offers an important guide to Petri net (PN) models and methods for supervisory control and system scheduling of resource allocation systems (RASs). Resource allocation systems are common in automated manufacturing systems, project management systems, cloud data centers, and software engineering systems. The authors—two experts on the topic—present a definition, techniques, models, and state-of-the art applications of supervisory control and scheduling problems. The book introduces the basic concepts and research background on resource allocation systems and Petri nets. The authors then focus on the deadlock-free supervisor synthesis for RASs using Petri nets. The book also investigates the heuristic scheduling of RASs based on timed Petri nets. Conclusions and open problems are provided in the last section of the book. This important book: Includes multiple methods for supervisory control and scheduling with reachability graphs, and provides illustrative examples Reveals how to accelerate the supervisory controller design and system scheduling of RASs based on PN reachability graphs, with optimal or near-optimal results Highlights both solution quality and computational speed in RAS deadlock handling and system scheduling Written for researchers, engineers, scientists, and professionals in system planning and control, engineering, operation, and management, Supervisory Control and Scheduling of Resource Allocation Systems provides an essential guide to the supervisory control and scheduling of resource allocation systems (RASs) using Petri net reachability graphs, which allow for multiple resource acquisitions and flexible routings.
Sustainable Manufacturing Systems Learn more about energy efficiency in traditional and advanced manufacturing settings with this leading and authoritative resource Sustainable Manufacturing Systems: An Energy Perspective delivers a comprehensive analysis of energy efficiency in sustainable manufacturing. The book presents manufacturing modeling methods and energy efficiency evaluation and improvement methods for different manufacturing systems. It allows industry professionals to understand the methodologies and techniques being embraced around the world that lead to advanced energy management. The book offers readers a comprehensive and systematic theoretical foundation for novel manufacturing system modeling, analysis, and control. It concludes with a summary of the insights and applications contained within and a discussion of future research issues that have yet to be grappled with. Sustainable Manufacturing Systems answers the questions that energy customers, managers, decision makers, and researchers have been asking about sustainable manufacturing. The book’s release coincides with recent and profound advances in smart grid applications and will serve as a practical tool to assist industrial engineers in furthering the green revolution. Readers will also benefit from: A thorough introduction to energy efficiency in manufacturing systems, including the current state of research and research methodologies An exploration of the development of manufacturing methodologies, including mathematical modeling for manufacturing systems and energy efficiency characterization in manufacturing systems An analysis of the applications of various methodologies, including electricity demand response for manufacturing systems and energy control and optimization for manufacturing systems utilizing combined heat and power systems A discussion of energy efficiency in advanced manufacturing systems, like stereolithography additive manufacturing and cellulosic biofuel manufacturing systems Perfect for researchers, undergraduate students, and graduate students in engineering disciplines, especially for those majoring in industrial, mechanical, electrical, and environmental engineering, Sustainable Manufacturing Systems will also earn a place in the libraries of management and business students interested in manufacturing system cost performance and energy management.
Infrastructure Robotics Illuminating resource presenting commonly used robotic methodologies and technologies, with recent developments and clear application examples across different project types Infrastructure Robotics presents state-of-the-art research in infrastructure robotics and key methodologies that enable the development of intelligent robots for operation in civil infrastructure environments, describing sensing, perception, localization, map building, environmental and operation awareness, motion and task planning, design methodologies, robot assistance paradigms, and physical human-robot collaboration. The text also presents many case studies of robotic systems developed for real-world applications in maintaining various civil infrastructures, including steel bridges, tunnels, underground water mains, underwater structures, and sewer pipes. In addition, later chapters discuss lessons learned in deployment of intelligent robots in practical applications overall. Infrastructure Robotics provides a timely and thorough treatment of the subject pertaining to recent developments, such as computer vision and machine learning techniques that have been used in inspection and condition assessment of critical civil infrastructures, including bridges, tunnels, and more. Written by highly qualified contributors with significant experience in both academia and industry, Infrastructure Robotics covers topics such as: Design methods for application of robots in civil infrastructure inspired by biological systems including ants, inchworms, and humans Fundamental aspects of research on intelligent robotic co-workers for human-robot collaborative operations The ROBO-SPECT European project and a robotized alternative to manual tunnel structural inspection and assessment Wider context for the use of additive manufacturing techniques on construction sites Infrastructure Robotics is an essential resource for researchers, engineers, and graduate students in related fields. Professionals in civil engineering, asset management, and project management who wish to be on the cutting edge of the future of their industries will also benefit from the text.