Optimal State Estimation For Process Monitoring Fault Diagnosis And Control
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Optimal State Estimation for Process Monitoring, Fault Diagnosis and Control
Optimal State Estimation for Process Monitoring, Fault Diagnosis and Control presents various mechanistic model based state estimators and data-driven model based state estimators with a special emphasis on their development and applications to process monitoring, fault diagnosis and control. The design and analysis of different state estimators are highlighted with a number of applications and case studies concerning to various real chemical and biochemical processes. The book starts with the introduction of basic concepts, extending to classical methods and successively leading to advances in this field. Design and implementation of various classical and advanced state estimation methods to solve a wide variety of problems makes this book immensely useful for the audience working in different disciplines in academics, research and industry in areas concerning to process monitoring, fault diagnosis, control and related disciplines. - Describes various classical and advanced versions of mechanistic model based state estimation algorithms - Describes various data-driven model based state estimation techniques - Highlights a number of real applications of mechanistic model based and data-driven model based state estimators/soft sensors - Beneficial to those associated with process monitoring, fault diagnosis, online optimization, control and related areas
Towards Green Hydrogen Generation
Readers will find a multidisciplinary approach elucidating all the important features of green hydrogen so that science researchers and energy engineers as well as those in economics, political science and international relations, will also find value. Energy sources and generation is the foremost concern of all governments, NGOs, and activist groups. With Green New Deals and reduced or net zero emission goals being implemented on a global scale, the quest for economic, scalable, efficient, and sustainable energy systems has reached a fever pitch. No one energy source ticks all the boxes and new energy technologies are being developed all the time as potential disruptors. Enter green hydrogen with zero emissions. Hydrogen is a rare gas in nature and is often found together with natural gas. While hydrogen is the most abundant element in the known universe, molecular hydrogen is very rare in nature and needs to be produced—and produced in large quantities, if we are serious about the Green Deal. This book has been organized into three parts to introduce and discuss these crucial topics. Part I discusses the Green Deal and the current state and challenges encountered in the industrialization of green hydrogen production, as well as related politics. Chapters in this section include how to decarbonize the energy industry with green hydrogen, and one that describes a gradual shift in the approach of hydrogen production technologies from non-renewable to renewable. Part II is devoted to carbon capturing and hydrogen. Chapters on biomass mass waste-to-hydrogen conversion and related efficient and sustainable hydrogen storage pathways, life cycle assessment for eco-design of biohydrogen factory by microalgae, and metal oxide-based carbon capture technologies are all addressed in this section. The third and final part of the book was designed to present all features of green hydrogen generation. Chapters include PEM water electrolysis and other electrolyzers, wind-driven hydrogen production, and bifunctional electrocatalysts-driven hybrid water splitting, are introduced and thoroughly discussed. Audience This book is directed to researchers and industry professionals in energy engineering, chemistry, physics, materials science, and chemical engineering, as well as energy policymakers, energy economists, and others in the social sciences.
Advances in Process Control with Real Applications
Advances in Process Control with Real Applications presents various advanced controllers, including the formulation, design, and implementation of various advanced control strategies for a wide variety of processes. These strategies include generalized predictive control with and without constraints; linear and nonlinear model predictive control; dynamic matrix control; nonlinear control, such as generic model control, globally linearizing control, and nonlinear internal model control; optimal and optimizing control; inferential control; intelligent control based on fuzzy reasoning and neural networks; and controllers based on stochastic and evolutionary optimization.This book will be highly beneficial to students, researchers, and industry professionals working in process design, process monitoring, process systems engineering, process operations and control, and related areas. - Describes various advanced controllers for the control of complex nonlinear processes - Provides the fundamentals, algorithms, approaches, control strategies, and implementation procedures systematically - Highlights the significance and importance of advanced process control with many real applications