Sensitivity Analysis of Optimal Control Motivated by Model Predictive Control PDF Download

Author: Lars Grüne
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Author: Lars Grüne
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Author:
Publisher: Elsevier
ISBN: 0323853390
Category : Mathematics
Languages : en
Pages : 596

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Book Description
Numerical Control: Part A, Volume 23 in the Handbook of Numerical Analysis series, highlights new advances in the field, with this new volume presenting interesting chapters written by an international board of authors. Chapters in this volume include Numerics for finite-dimensional control systems, Moments and convex optimization for analysis and control of nonlinear PDEs, The turnpike property in optimal control, Structure-Preserving Numerical Schemes for Hamiltonian Dynamics, Optimal Control of PDEs and FE-Approximation, Filtration techniques for the uniform controllability of semi-discrete hyperbolic equations, Numerical controllability properties of fractional partial differential equations, Optimal Control, Numerics, and Applications of Fractional PDEs, and much more. Provides the authority and expertise of leading contributors from an international board of authors Presents the latest release in the Handbook of Numerical Analysis series Updated release includes the latest information on Numerical Control

Author: Timm Faulwasser
Publisher: Springer Nature
ISBN: 3030632814
Category : Science
Languages : en
Pages : 250

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This book focuses on distributed and economic Model Predictive Control (MPC) with applications in different fields. MPC is one of the most successful advanced control methodologies due to the simplicity of the basic idea (measure the current state, predict and optimize the future behavior of the plant to determine an input signal, and repeat this procedure ad infinitum) and its capability to deal with constrained nonlinear multi-input multi-output systems. While the basic idea is simple, the rigorous analysis of the MPC closed loop can be quite involved. Here, distributed means that either the computation is distributed to meet real-time requirements for (very) large-scale systems or that distributed agents act autonomously while being coupled via the constraints and/or the control objective. In the latter case, communication is necessary to maintain feasibility or to recover system-wide optimal performance. The term economic refers to general control tasks and, thus, goes beyond the typically predominant control objective of set-point stabilization. Here, recently developed concepts like (strict) dissipativity of optimal control problems or turnpike properties play a crucial role. The book collects research and survey articles on recent ideas and it provides perspectives on current trends in nonlinear model predictive control. Indeed, the book is the outcome of a series of six workshops funded by the German Research Foundation (DFG) involving early-stage career scientists from different countries and from leading European industry stakeholders.

Author: Jinfeng Liu
Publisher: MDPI
ISBN: 303897420X
Category : Technology & Engineering
Languages : en
Pages : 231

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This book is a printed edition of the Special Issue "New Directions on Model Predictive Control" that was published in Mathematics

Author: Francesco Borrelli
Publisher: Cambridge University Press
ISBN: 1108158293
Category : Mathematics
Languages : en
Pages : 447

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Book Description
Model Predictive Control (MPC), the dominant advanced control approach in industry over the past twenty-five years, is presented comprehensively in this unique book. With a simple, unified approach, and with attention to real-time implementation, it covers predictive control theory including the stability, feasibility, and robustness of MPC controllers. The theory of explicit MPC, where the nonlinear optimal feedback controller can be calculated efficiently, is presented in the context of linear systems with linear constraints, switched linear systems, and, more generally, linear hybrid systems. Drawing upon years of practical experience and using numerous examples and illustrative applications, the authors discuss the techniques required to design predictive control laws, including algorithms for polyhedral manipulations, mathematical and multiparametric programming and how to validate the theoretical properties and to implement predictive control policies. The most important algorithms feature in an accompanying free online MATLAB toolbox, which allows easy access to sample solutions. Predictive Control for Linear and Hybrid Systems is an ideal reference for graduate, postgraduate and advanced control practitioners interested in theory and/or implementation aspects of predictive control.

Author: Andrzej Wierzbicki
Publisher: Elsevier Publishing Company
ISBN:
Category : Technology & Engineering
Languages : en
Pages : 424

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Mathematical models. Sensitivity analysis of mathematical models. Optimization and optimal control. Sensitivity analysis of the optimal control systems.

Author: A L Dontchev
Publisher: Springer
ISBN: 9783662180242
Category :
Languages : en
Pages : 168

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Author: Lalo Magni
Publisher: Società Editrice Esculapio
ISBN:
Category : Technology & Engineering
Languages : en
Pages : 211

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Book Description
This textbook is designed for an advanced course in control theory. The purpose of Chapter 1 is to introduce some results on the stability of dynamic systems achieved with the Lyapunov theory, and on its use for the synthesis of nonlinear control laws. The definition of norms and gains of dynamic systems is reported in Chapter 2 to provide the reader with the mathematical tools required in the following chapters. Some basic techniques for the analysis and the control of single-input, single-output systems are recalled in Chapter 3 to motivate the introduction, in the following chapters, of synthesis techniques for multi-input, multi-output systems. The analysis of multivariable systems, in terms of poles and zeros, manipulation rules of block diagrams, frequency response, stability of the feedback system, and static and dynamic performance, are discussed in Chapters 4 and 5. In Chapter 6 the pole-placement approach for the synthesis of state feedback control laws and state observers is described. Optimal control synthesis techniques for continuous- time systems are presented from Chapter 7 to 10. Specifically, the Linear Quadratic control method, the Kalman filter and the LQG control are widely described together with their main properties. These results are then extended to the discrete-time case in Chapter 11. The main algorithms and results of Model Predictive Control are finally presented in Chapter 12. Some useful mathematical notions are summarized in the Appendix. • stability • Lyapunov theory • multivariable systems • pole placement • state observers • optimal control • linear quadratic control • Kalman filter • LQG control • model predictive control

Author: Anton Hendrik Evers
Publisher:
ISBN:
Category : Control theory
Languages : en
Pages : 91

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