Oversized hardcover, xxxiii + 267 pages, NOT ex-library. Gentle internal creasing; interior is clean and bright throughout, with unmarked text, free of inscriptions and stamps, firmly bound. Small areas of cosmetic damage along the upper edges of boards. Issued without a dust jacket. -- The book provides a detailed and practical exploration of multivariable predictive control (MPC) techniques, with a focus on real-world industrial applications. It offers a comprehensive overview of MPC theory and showcases how it is implemented across various industries to improve process control, efficiency, and operational performance. Through practical case studies and examples, Lahiri demonstrates how MPC can be applied to handle complex control problems involving multiple variables, ensuring optimal performance in industries such as chemical processing, oil and gas, manufacturing, and power generation. This book is designed for engineers, researchers, and practitioners seeking to understand the intricacies of multivariable predictive control and its potential for enhancing industrial processes. The content spans from the fundamental principles of MPC to advanced applications, making it a valuable resource for both beginners and experienced professionals in the field. Key topics include model-based control strategies, system dynamics, algorithm implementation, performance optimization, and the integration of predictive control into existing industrial processes. With its practical orientation, Multivariable Predictive Control serves as a guide for improving process stability, reducing operational costs, and achieving higher efficiency in modern industrial environments.

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Detalles bibliogr�ficos

T�tulo: Multivariable Predictive Control: Applications in Industry
Editor: Wiley
Fecha de publicaci�n: 2017
Idioma: Ingl�s
ISBN 10: 1119243602
ISBN 13: 9781119243601
Encuadernaci�n: Hardcover
Edici�n: 1st Edition
Estado: Good

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Sinopsis

A guide to all practical aspects of building, implementing, managing, and maintaining MPC applications in industrial plants

Multivariable Predictive Control: Applications in Industry provides engineers with a thorough understanding of all practical aspects of multivariate predictive control (MPC) applications, as well as expert guidance on how to derive maximum benefit from those systems. Short on theory and long on step-by-step information, it covers everything plant process engineers and control engineers need to know about building, deploying, and managing MPC applications in their companies.

MPC has more than proven itself to be one the most important tools for optimising plant operations on an ongoing basis. Companies, worldwide, across a range of industries are successfully using MPC systems to optimise materials and utility consumption, reduce waste, minimise pollution, and maximise production. Unfortunately, due in part to the lack of practical references, plant engineers are often at a loss as to how to manage and maintain MPC systems once the applications have been installed and the consultants and vendors’ reps have left the plant. Written by a chemical engineer with two decades of experience in operations and technical services at petrochemical companies, this book fills that regrettable gap in the professional literature.

Provides a cost-benefit analysis of typical MPC projects and reviews commercially available MPC software packages
Details software implementation steps, as well as techniques for successfully evaluating and monitoring software performance once it has been installed
Features case studies and real-world examples from industries, worldwide, illustrating the advantages and common pitfalls of MPC systems
Describes MPC application failures in an array of companies, exposes the root causes of those failures, and offers proven safeguards and corrective measures for avoiding similar failures

Multivariable Predictive Control: Applications in Industry is an indispensable resource for plant process engineers and control engineers working in chemical plants, petrochemical companies, and oil refineries in which MPC systems already are operational, or where MPC implementations are being considering.

Acerca del autor

Sandip Kumar Lahiri, PhD, is a chemical engineer with more than twenty one years of experience in operations and technical services at leading petrochemical industries around the globe. His areas of expertise include simulation, process modelling, artificial intelligence and neural networks in process industry, APC, soft sensor, and slurry flow modelling.

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