東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Model predictive control = engineeri...

Daniilidis, Aris.

Linked to FindBook

Google Book

Amazon

博客來

Model predictive control = engineering methods for economists /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Model predictive control/ edited by Aris Daniilidis ... [et al.].
Reminder of title:	engineering methods for economists /
other author:	Daniilidis, Aris.
Published:	Cham :Springer Nature Switzerland : : 2025.,
Description:	xii, 224 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Chapter 1. Multi-horizon MPC and Its Application to theIntegrated Power and Thermal Management ofElectriﬁed Vehicles (Qiuhao Hu) -- Chapter 2. Data/Moment-Driven Approaches for FastPredictive Control of Collective Dynamics (Giacomo Albi) -- Chapter 3. Finite-Dimensional Receding Horizon Control ofLinear Time-Varying Parabolic PDEs: StabilityAnalysis and Model-Order Reduction (Behzad Azmi) -- Chapter 4. Solving Hybrid Model Predictive ControlProblems via a Mixed-Integer Approach (Iman Nodozi) -- Chapter 5. nMPyC - A Python Package for Solving OptimalControl Problems via Model Predictive Control (Jonas Schießl) -- Chapter 6. Controllability of Continuous Networks and aKernel-Based Learning Approximation (Michael Herty) -- Chapter 7. Economic Model Predictive Control as aSolution to Markov Decision Processes (Dirk Reinhardt) -- Chapter 8. Reinforcement Learning with Guarantees (Mario Zanon).
Contained By:	Springer Nature eBook
Subject:	Predictive control. -
Online resource:	https://doi.org/10.1007/978-3-031-85256-5
ISBN:	9783031852565

Model predictive control = engineering methods for economists /
Model predictive controlengineering methods for economists /[electronic resource] :edited by Aris Daniilidis ... [et al.]. - Cham :Springer Nature Switzerland :2025. - xii, 224 p. :ill. (some col.), digital ;24 cm. - Dynamic modeling and econometrics in economics and finance,v. 312363-8370 ;. - Dynamic modeling and econometrics in economics and finance ;v. 31..

Chapter 1. Multi-horizon MPC and Its Application to theIntegrated Power and Thermal Management ofElectriﬁed Vehicles (Qiuhao Hu) -- Chapter 2. Data/Moment-Driven Approaches for FastPredictive Control of Collective Dynamics (Giacomo Albi) -- Chapter 3. Finite-Dimensional Receding Horizon Control ofLinear Time-Varying Parabolic PDEs: StabilityAnalysis and Model-Order Reduction (Behzad Azmi) -- Chapter 4. Solving Hybrid Model Predictive ControlProblems via a Mixed-Integer Approach (Iman Nodozi) -- Chapter 5. nMPyC - A Python Package for Solving OptimalControl Problems via Model Predictive Control (Jonas Schießl) -- Chapter 6. Controllability of Continuous Networks and aKernel-Based Learning Approximation (Michael Herty) -- Chapter 7. Economic Model Predictive Control as aSolution to Markov Decision Processes (Dirk Reinhardt) -- Chapter 8. Reinforcement Learning with Guarantees (Mario Zanon).

The book explores the field of model predictive control (MPC). It reports on the latest developments in MPC, current applications, and presents various subfields of MPC. The book features topics such as uncertain and stochastic MPC variants, learning and neural network approaches, easy-to-use numerical implementations as well as multi-agent systems and scheduling and coordination tasks. While MPC is rooted in engineering science, this book illustrates the potential of using MPC theory and methods in non-engineering sciences and applications such as economics, finance, and environmental sciences.

ISBN: 9783031852565

Standard No.: 10.1007/978-3-031-85256-5doiSubjects--Topical Terms:

667592
Predictive control.

LC Class. No.: TJ217.6

Dewey Class. No.: 629.8

Model predictive control = engineering methods for economists /
LDR:02657nmm a2200349 a 4500 001 2412083
003 DE-He213
005 20250607130246.0
006 m d
007 cr nn 008maaau
008 260204s2025 sz s 0 eng d
020 $a 9783031852565 $q (electronic bk.)
020 $a 9783031852558 $q (paper)
024 7 $a 10.1007/978-3-031-85256-5 $2 doi
035 $a 978-3-031-85256-5
040 $a GP $c GP
041 0 $a eng
050 4 $a TJ217.6
072 7 $a KCA $2 bicssc
072 7 $a BUS021000 $2 bisacsh
072 7 $a KCA $2 thema
082 0 4 $a 629.8 $2 23
090 $a TJ217.6 $b .M689 2025
245 0 0 $a Model predictive control $h [electronic resource] : $b engineering methods for economists / $c edited by Aris Daniilidis ... [et al.].
260 $a Cham : $b Springer Nature Switzerland : $b Imprint: Springer, $c 2025.
300 $a xii, 224 p. : $b ill. (some col.), digital ; $c 24 cm.
338 $a online resource $b cr $2 rdacarrier
490 1 $a Dynamic modeling and econometrics in economics and finance, $x 2363-8370 ; $v v. 31
505 0 $a Chapter 1. Multi-horizon MPC and Its Application to theIntegrated Power and Thermal Management ofElectriﬁed Vehicles (Qiuhao Hu) -- Chapter 2. Data/Moment-Driven Approaches for FastPredictive Control of Collective Dynamics (Giacomo Albi) -- Chapter 3. Finite-Dimensional Receding Horizon Control ofLinear Time-Varying Parabolic PDEs: StabilityAnalysis and Model-Order Reduction (Behzad Azmi) -- Chapter 4. Solving Hybrid Model Predictive ControlProblems via a Mixed-Integer Approach (Iman Nodozi) -- Chapter 5. nMPyC - A Python Package for Solving OptimalControl Problems via Model Predictive Control (Jonas Schießl) -- Chapter 6. Controllability of Continuous Networks and aKernel-Based Learning Approximation (Michael Herty) -- Chapter 7. Economic Model Predictive Control as aSolution to Markov Decision Processes (Dirk Reinhardt) -- Chapter 8. Reinforcement Learning with Guarantees (Mario Zanon).
520 $a The book explores the field of model predictive control (MPC). It reports on the latest developments in MPC, current applications, and presents various subfields of MPC. The book features topics such as uncertain and stochastic MPC variants, learning and neural network approaches, easy-to-use numerical implementations as well as multi-agent systems and scheduling and coordination tasks. While MPC is rooted in engineering science, this book illustrates the potential of using MPC theory and methods in non-engineering sciences and applications such as economics, finance, and environmental sciences.
650 0 $a Predictive control. $3 667592
650 1 4 $a Quantitative Economics. $3 3538570
650 2 4 $a Operations Research and Decision Theory. $3 3591727
650 2 4 $a Mathematics in Business, Economics and Finance. $3 3538573
650 2 4 $a Stochastic Systems and Control. $3 3596108
650 2 4 $a Control and Systems Theory. $3 3381515
700 1 $a Daniilidis, Aris. $3 3787051
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Dynamic modeling and econometrics in economics and finance ; $v v. 31. $3 3787052
856 4 0 $u https://doi.org/10.1007/978-3-031-85256-5
950 $a Economics and Finance (SpringerNature-41170)