Model Predictive Control Engineering Methods for Economists /

Model Predictive Control Engineering Methods for Economists /

Manylion Llyfryddiaeth
Awdur Corfforaethol: SpringerLink (Online service)
Awduron Eraill: Daniilidis, Aris (Golygydd), Grüne, Lars (Golygydd), Haunschmied, Josef (Golygydd), Tragler, Gernot (Golygydd)
Crynodeb:XII, 224 p. 148 illus., 124 illus. in color.
text
Iaith:Saesneg
Cyhoeddwyd: Cham : Springer Nature Switzerland : Imprint: Springer, 2025.
Rhifyn:1st ed. 2025.
Cyfres:Dynamic Modeling and Econometrics in Economics and Finance, 31
Pynciau:
Econometrics.
Operations research.
Social sciences > Mathematics.
Stochastic processes.
Control engineering.
Quantitative Economics.
Operations Research and Decision Theory.
Mathematics in Business, Economics and Finance.
Stochastic Systems and Control.
Control and Systems Theory.
Mynediad Ar-lein:https://doi.org/10.1007/978-3-031-85256-5
Fformat: Electronig Llyfr
Tabl Cynhwysion:
  • 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).

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