Bücher der Reihe Advances in Industrial Control

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.

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 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.

The authors provide a modular simulator to be run in MATLAB/Simulink (R), for readers to create their own microgrids using the blocks supplied, in order to replicate the examples provided in the book and to develop and validate control algorithms on existing or projected microgrids.