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020			_a9783030680107
024	7		_a10.1007/978-3-030-68010-7 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aTJ785 _b2021 EB
100	1		_aRajasingham, Thivaharan Albin _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9682066
245	1	0	_aNonlinear Model Predictive Control of Combustion Engines : _bFrom Fundamentals to Applications _cby Thivaharan Albin Rajasingham.
250			_aFirst edition 2021
264		1	_aCham _bSpringer International Pulishing _c2021
300			_a1 recurso en línea (XVII, 330 páginas) _b134 ilustraciones, 80 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_aarchivo de texto _bPDF
490	0		_aAdvances in Industrial Control _x2193-1577
490	0		_aIntelligent Technologies and Robotics (SpringerNature-42732)
490	0		_aIntelligent Technologies and Robotics (R0) (SpringerNature-43728)
505	0		_aPart I: Fundamentals for Engine Control Based on Nonlinear Model Predictive Control -- Introduction -- Nonlinear Model Predictive Control -- NMPC-Based Engine Control -- Part II: Airpath Control -- Introduction to Airpath Control -- Reduced-Order Modeling -- In-Depth Case Study I: Two-Stage Turbocharging for SI Engines -- In-Depth Case Study II: Dual-Loop EGR for Compression Ignition Engines -- Part III: Combustion Control for Premixed Charge Compression Ignition Engines -- Reduced-Order Modeling -- In-Depth Case Study III: Premixed Compression Ignition Engines with Diesel-like Fuels -- In-Depth Case Study IV: Premixed Compression Ignition Engines with Gasoline-like Fuels.
520	3		_aThis 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.
988			_aSpringer_Robotics_2021
650		7	_2embne _aMotores de combustión interna _9142270
776	0	8	_iPrinted edition: _z9783030680091
776	0	8	_iPrinted edition: _z9783030680114
776	0	8	_iPrinted edition: _z9783030680121
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-68010-7 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE