Nonlinear Model Predictive Control of Combustion Engines: From Fundamentals to Applications (Advances in Industrial Control) - Tapa blanda

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Thivaharan Albin Rajasingham received his Diploma in 2008 from the Technical University of Braunschweig (Germany) and the University of Waterloo (Canada), and his PhD in Mechanical Engineering in 2013 from RWTH Aachen University. From 2013 – 2016 he worked as a senior engineer at the Institute of Automatic Control at RWTH Aachen University. Afterwards, from 2017 – 2019, he worked as a senior researcher and lecturer at the Institute of Dynamic Systems and Control at ETH Zürich, Switzerland. In 2019 he joined Embotech AG as the head of industrial automation solutions.

In his career, Dr. Albin Rajasingham has focused on the application of nonlinear model predictive control to complex systems. He has won various prizes and has been awarded several major research grants for interdisciplinary research projects, such as spokesperson of the Research Unit 2401 “Optimization-based Multiscale Control of Low-Temperature Combustion Engines” funded by the German Research Foundation (DFG). His work has resulted in a considerable amount of publications and patents.

De la contraportada

This book provides an overview of the nonlinear model predictive control (NMPC) concept for application to innovative combustion engines. Readers can use this book to become more expert in advanced combustion engine control and to develop and implement their own NMPC algorithms to solve challenging control tasks in the field. The significance of the advantages and relevancy for practice is demonstrated by real-world engine and vehicle application examples. 

The author provides an overview of fundamental engine control systems, and addresses emerging control problems, showing how they can be solved with NMPC. The implementation of NMPC involves various development steps, including:

•      reduced-order modeling of the process;

•      analysis of system dynamics;

•      formulation of the optimization problem; and

•      real-time feasible numerical solution of the optimization problem.

Readers will see the entire process of these steps, from the fundamentals to several innovative applications. The application examples highlight the actual difficulties and advantages when implementing NMPC for engine control applications. 

Nonlinear Model Predictive Control of Combustion Engines targets engineers and researchers in academia and industry working in the field of engine control. The book is laid out in a structured and easy-to-read manner, supported by code examples in MATLAB®/Simulink®, thus expanding its readership to students and academics who would like to understand the fundamental concepts of NMPC.

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.