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Titlebook: Nonlinear Model Predictive Control of Combustion Engines; From Fundamentals to Thivaharan Albin Rajasingham Book 2021 Springer Nature Switz

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书目名称Nonlinear Model Predictive Control of Combustion Engines
副标题From Fundamentals to
编辑Thivaharan Albin Rajasingham
视频video
概述Covers a wide range of combustion engine control problems from innovative airpath concepts to new combustion concepts.Provides readers with a systematic insight into the modeling and optimization-base
丛书名称Advances in Industrial Control
图书封面Titlebook: Nonlinear Model Predictive Control of Combustion Engines; From Fundamentals to Thivaharan Albin Rajasingham Book 2021 Springer Nature Switz
描述.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 Engin
出版日期Book 2021
关键词Control of Combustion Engines; Model Predictive Control; Reduced-order Modeling of Combustion Engines;
版次1
doihttps://doi.org/10.1007/978-3-030-68010-7
isbn_softcover978-3-030-68012-1
isbn_ebook978-3-030-68010-7Series ISSN 1430-9491 Series E-ISSN 2193-1577
issn_series 1430-9491
copyrightSpringer Nature Switzerland AG 2021
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Linear Model Predictive Controltates along with a quadratic cost function and linear constraints. This chapter presents an overview of various aspects of LMPC. First, the unconstrained LMPC will be explained, including the solution of the optimization problem and the resulting control structure. Based on these results, the extens
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Nonlinear Model Predictive Controll predictive control (LMPC) method. For engine control problems, the consideration of their nonlinear process behavior is particularly important as their treatment as a linearized system is often not sufficient. In this chapter, the fundamentals of NMPC are presented. A special focus is set on the r
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SI and CI Engine Control Architecturesengine control is given. A suitable architecture is presented which can be used to handle the demanding requirements on process control. By the use of hierarchization and modularization, the complex interaction of the various components can be tackled. For both the SI and the CI engine, a typical ha
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Low-Temperature Combustion Engine Controlative combustion concept for use in engine systems. They hold promise to lower pollutant emissions while achieving a high efficiency. The working principle is based on the autoignition of a highly premixed charge. These properties come along with increased demands for the process control. In this ch
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Fundamentals of Control-Oriented Air Path Modelingiven. To realize appropriate real-time optimization, a suitable trade-off is needed between the accuracy of a model and its computational complexity. Additionally, if gradient-based methods are applied for a numerical solution of the optimization problem, models are required that are continuously di
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