Bøger i Advances in Industrial Control serien

This book provides a summary of the essential knowledge and working processes involved with control of rotating equipment including:machine characteristics;overall control strategies;detailed design; andbest practices.Emphasis is placed on the role of pumps and compressors as part of the overall process flow rather than treating them in isolation as this tends to optimize energy efficiency.Readers are made aware of the critical roles of rotating equipment and are given a good understanding of their dynamic behaviors, including surge/choke. The author imparts the practical know-how and skills involved in the design and implementation of capacity and anti-surge control and safe-guarding logic. Furthermore, the book discusses real-time monitoring of solutions based on operational requirements, dynamic models for control of supply and demand, cause-and-effect relationships, the useof online and offline data, and collaboration with other engineering disciplines. The text facilitates support for the day-to-day operation of in-house open-platform compressor control applications, encouraging the growth of analytic skills in troubleshooting and fixing common problems; it also inculcates a basic understanding of the principles of third-party proprietary technologies and supports decision-making between in-house and third-party solutions.Process engineers working in the oil-and-gas, refining, petrochemical, and chemical industries who bear responsibility for designing control solutions involving pumps and compressors will find this book an invaluable source of practical advice. This book also helps engineers working on design and maintenance of rotating equipment to understand the perspectives and requirements of process control.

Process Control details the core knowledge and practical skills that a successful process control practitioner needs. It explains the essential technologies that are in use in current industrial practice or which may be wanting for the future. The book focuses on practical considerations, not only on those that make a control solution work, but also on those that prevent it from failing, especially for complex control loops and plant-wide control solutions.After discussing the indispensable role of control in modern process industries, the authors concentrate on the skills required for process analysis, control design, and troubleshooting. One of the first books to provide a systematic approach and structured methodology for process analysis and control design, Process Control illustrates that methodology with many practical examples that cover process control, equipment control, and control calculations derived from real projects and applications. The book uses 229 drawings and 83 tables to make the concepts it presents more intuitive and its methodology easy to follow.Process Control will help the practising control engineer to benefit from a wealth of practical experience and good ideas on how to make control work in the real world and students training to take up roles in process control are shown the applied relevance of control theory in the efficient functioning of industrial plant and the considerations needed to make it work.Advances in Industrial Control reports and encourages 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 industrial control.

This book offers a thorough introduction to the basics and scientific and technological innovations involved in the modern study of reinforcement-learning-based feedback control. The authors address a wide variety of systems including work on nonlinear, networked, multi-agent and multi-player systems. A concise description of classical reinforcement learning (RL), the basics of optimal control with dynamic programming and network control architectures, and a brief introduction to typical algorithms build the foundation for the remainder of the book. Extensive research on data-driven robust control for nonlinear systems with unknown dynamics and multi-player systems follows. Data-driven optimal control of networked single- and multi-player systems leads readers into the development of novel RL algorithms with increased learning efficiency. The book concludes with a treatment of how these RL algorithms can achieve optimal synchronization policies for multi-agentsystems with unknown model parameters and how game RL can solve problems of optimal operation in various process industries. Illustrative numerical examples and complex process control applications emphasize the realistic usefulness of the algorithms discussed. The combination of practical algorithms, theoretical analysis and comprehensive examples presented in Reinforcement Learning will interest researchers and practitioners studying or using optimal and adaptive control, machine learning, artificial intelligence, and operations research, whether advancing the theory or applying it in mineral-process, chemical-process, power-supply or other industries.

This book provides a thorough and fresh treatment of the control of innovative variable-geometry vehicle suspension systems. A deep survey on the topic, which covers the varying types of existing variable-geometry suspension solutions, introduces the study. The book discusses three important aspects of the subject:¿ robust control design;¿ nonlinear system analysis; and¿ integration of learning and control methods.The importance of variable-geometry suspensions and the effectiveness of design methods implemented in the autonomous functionalities of electric vehicles¿functionalities like independent steering and torque vectoring¿are illustrated. The authors detail the theoretical background of modeling, control design, and analysis for each functionality. The theoretical results achieved through simulation examples and hardware-in-the-loop scenarios are confirmed. The book highlights emerging ideas of applying machine-learning-based methods in the control system with guarantees on safety performance. The authors propose novel control methods, based on the theory of robust linear parameter-varying systems, with examples for various suspension systems.Academic researchers interested in automotive systems and their counterparts involved in industrial research and development will find much to interest them in the eleven chapters of Control of Variable-Geometry Vehicle Suspensions.

The main focus of this book is a pair of cooperative control problems: consensus and cooperative output regulation. Its emphasis is on complex multi-agent systems characterized by strong nonlinearity, large uncertainty, heterogeneity, external disturbances and jointly connected switching communication topologies. The cooperative output regulation problem is a generalization of the classical output regulation problem to multi-agent systems and it offers a general framework for handling a variety of cooperative control problems such as consensus, formation, tracking and disturbance rejection. The book strikes a balance between rigorous mathematical proof and engineering practicality. Every design method is systematically presented together with illustrative examples and all the designs are validated by computer simulation. The methods presented are applied to several practical problems, among them the leader-following consensus problem of multiple Euler-Lagrange systems, attitude synchronization of multiple rigid-body systems, and power regulation of microgrids. The book gives a detailed exposition of two approaches to the design of distributed control laws for complex multi-agent systems-the distributed-observer and distributed-internal-model approaches. Mastering both will enhance a reader's ability to deal with a variety of complex real-world problems. Cooperative Control of Multi-agent Systems can be used as a textbook for graduate students in engineering, sciences, and mathematics, and can also serve as a reference book for practitioners and theorists in both industry and academia. Some knowledge of the fundamentals of linear algebra, calculus, and linear systems are needed to gain maximum benefit from this book. Advances in Industrial Control reports and encourages 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 industrial control.

This book focuses on pneumatic servo systems analysis, control and application in robotic systems. The pneumatic servo systems are composed by pneumatic artificial muscles or cylinders, which are two important pneumatic actuators in industrial application. The active disturbance rejection control technique is used effectively to solve strong nonlinearity and uncertain factors for the pneumatic servo systems. Nonlinear feedback control, back-stepping control, finite-time control, sliding mode control and several other control laws are proposed to make the pneumatic servo systems have better control performances. The book establishes a fundamental framework for this topic, while emphasizing the importance of integrated analysis. The book is intended for undergraduate and graduate students who are interested in this field and engineers working on the applications of pneumatic servo systems.Advances in Industrial Control reports and encourages 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 industrial control.

The presence of non-linearities, such as stiction and deadband, places limits on the performance of control valves. Indeed, in the process industries, stiction is the most common valve problem, and over the last decade numerous different techniques for overcoming it have been proposed.Detection and Diagnosis of Stiction in Control Loops represents a comprehensive presentation of these methods, including their principles, assumptions, strengths and drawbacks. Guidelines and working procedures are provided for the implementation of each method and MATLABbased software can be downloaded from www.ualberta.ca/~bhuang/stiction-book enabling readers to apply the methods to their own data. Methods for the limitation of stiction effects are proposed within the general context of: oscillation detection in control loops, stiction detection diagnosis; , stiction quantification and diagnosis of multiple faults.The state-of-the-art algorithms presented in this book are demonstrated and compared in industrial case studies of diverse origin - chemicals, building, mining, pulp and paper, mineral and metal processing. Industry-based engineers will find the book to be valuable guidance in increasing the performance of their control loops while academic researchers and graduate students interested in control performance and fault detection will discover a wealth of static-friction-related research and useful algorithms.

Model Predictive Control is an important technique used in the process control industries. It has developed considerably in the last few years, because it is the most general way of posing the process control problem in the time domain. The Model Predictive Control formulation integrates optimal control, stochastic control, control of processes with dead time, multivariable control and future references. The finite control horizon makes it possible to handle constraints and non linear processes in general which are frequently found in industry. Focusing on implementation issues for Model Predictive Controllers in industry, it fills the gap between the empirical way practitioners use control algorithms and the sometimes abstractly formulated techniques developed by researchers. The text is firmly based on material from lectures given to senior undergraduate and graduate students and articles written by the authors.

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 otTers an opportunity for researchers to present an extended exposition of such new work in all aspects of industrial control for wider and rapid dissemination. The time for nonlinear control to enter routine application seems to be approaching. Nonlinear control has had a long gestation period but much ofthe past has been concerned with methods that involve formal nonlinear functional model representations. It seems more likely that the breakthough will come through the use of other more flexible and amenable nonlinear system modelling tools. This Advances in Industrial Control monograph by Guoping Liu gives an excellent introduction to the type of new nonlinear system modelling methods currently being developed and used. Neural networks appear prominent in these new modelling directions. The monograph presents a systematic development of this exciting subject. It opens with a useful tutorial introductory chapter on the various tools to be used. In subsequent chapters Doctor Liu leads the reader through identification, and then onto nonlinear control using nonlinear system neural network representations.

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 wider and rapid dissemination. The last decade has seen considerable interest in reviving the fortunes of non­ linear control. In contrast to the approaches of the 60S, 70S and 80S a very pragmatic agenda for non-linear control is being pursued using the model-based predictive control paradigm. This text by R. Ansari and M. Tade gives an excellent synthesis of this new direction. Two strengths emphasized by the text are: (i) four applications found in refinery processes are used to give the text a firm practical continuity; (ii) a non-linear model-based control architecture is used to give the method a coherent theoretical framework.