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Download the fantastic book titled Explicit Nonlinear Model Predictive Control written by Alexandra Grancharova, available in its entirety in both PDF and EPUB formats for online reading. This page includes a concise summary, a preview of the book cover, and detailed information about "Explicit Nonlinear Model Predictive Control", which was released on 22 March 2012. We suggest perusing the summary before initiating your download. This book is a top selection for enthusiasts of the Technology & Engineering genre.

Summary of Explicit Nonlinear Model Predictive Control by Alexandra Grancharova PDF

Nonlinear Model Predictive Control (NMPC) has become the accepted methodology to solve complex control problems related to process industries. The main motivation behind explicit NMPC is that an explicit state feedback law avoids the need for executing a numerical optimization algorithm in real time. The benefits of an explicit solution, in addition to the efficient on-line computations, include also verifiability of the implementation and the possibility to design embedded control systems with low software and hardware complexity. This book considers the multi-parametric Nonlinear Programming (mp-NLP) approaches to explicit approximate NMPC of constrained nonlinear systems, developed by the authors, as well as their applications to various NMPC problem formulations and several case studies. The following types of nonlinear systems are considered, resulting in different NMPC problem formulations: ؠ Nonlinear systems described by first-principles models and nonlinear systems described by black-box models; - Nonlinear systems with continuous control inputs and nonlinear systems with quantized control inputs; - Nonlinear systems without uncertainty and nonlinear systems with uncertainties (polyhedral description of uncertainty and stochastic description of uncertainty); - Nonlinear systems, consisting of interconnected nonlinear sub-systems. The proposed mp-NLP approaches are illustrated with applications to several case studies, which are taken from diverse areas such as automotive mechatronics, compressor control, combustion plant control, reactor control, pH maintaining system control, cart and spring system control, and diving computers.


Detail About Explicit Nonlinear Model Predictive Control PDF

  • Author : Alexandra Grancharova
  • Publisher : Springer
  • Genre : Technology & Engineering
  • Total Pages : 241 pages
  • ISBN : 3642287808
  • PDF File Size : 48,5 Mb
  • Language : English
  • Rating : 4/5 from 21 reviews

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Explicit Nonlinear Model Predictive Control

Explicit Nonlinear Model Predictive Control
  • Publisher : Springer
  • File Size : 30,5 Mb
  • Release Date : 22 March 2012
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Nonlinear Model Predictive Control (NMPC) has become the accepted methodology to solve complex control problems related to process industries. The main motivation behind explicit NMPC is that an explicit state

Assessment and Future Directions of Nonlinear Model Predictive Control

Assessment and Future Directions of Nonlinear Model Predictive Control
  • Publisher : Springer
  • File Size : 34,6 Mb
  • Release Date : 08 September 2007
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Thepastthree decadeshaveseenrapiddevelopmentin the areaofmodelpred- tive control with respect to both theoretical and application aspects. Over these 30 years, model predictive control for linear systems has been widely applied, especially in the

Nonlinear Model Predictive Control

Nonlinear Model Predictive Control
  • Publisher : Springer Science & Business Media
  • File Size : 54,7 Mb
  • Release Date : 25 May 2009
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Over the past few years significant progress has been achieved in the field of nonlinear model predictive control (NMPC), also referred to as receding horizon control or moving horizon control.

Handbook of Model Predictive Control

Handbook of Model Predictive Control
  • Publisher : Springer
  • File Size : 38,8 Mb
  • Release Date : 01 September 2018
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Recent developments in model-predictive control promise remarkable opportunities for designing multi-input, multi-output control systems and improving the control of single-input, single-output systems. This volume provides a definitive survey of the

Nonlinear Model Predictive Control

Nonlinear Model Predictive Control
  • Publisher : Birkhäuser
  • File Size : 36,9 Mb
  • Release Date : 06 December 2012
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During the past decade model predictive control (MPC), also referred to as receding horizon control or moving horizon control, has become the preferred control strategy for quite a number of

Model Predictive Control

Model Predictive Control
  • Publisher : Springer
  • File Size : 21,7 Mb
  • Release Date : 14 August 2018
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This monograph introduces the authors’ work on model predictive control system design using extended state space and extended non-minimal state space approaches. It systematically describes model predictive control design for

Nonlinear Model Predictive Control of Combustion Engines

Nonlinear Model Predictive Control of Combustion Engines
  • Publisher : Springer Nature
  • File Size : 41,5 Mb
  • Release Date : 27 April 2021
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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

Predictive Control for Linear and Hybrid Systems

Predictive Control for Linear and Hybrid Systems
  • Publisher : Cambridge University Press
  • File Size : 53,5 Mb
  • Release Date : 22 June 2017
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With a simple approach that includes real-time applications and algorithms, this book covers the theory of model predictive control (MPC).