Model Predictive Control
Engineering Methods for Economists
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Beschreibung
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.
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.
Reports on the latest developments in MPC and current applications Illustrates applications of MPC methods in economics, finance, and environmental sciences Offers insights into how MPC is applied to engineering problems
Autor*in
Aris Daniilidis
Themen in »Model Predictive Control«
Economic Dynamics Control Systems Dynamical models Stochastic methods in Control Stabilization and Optimal Control Model Predictive Control Nonlinear Systems Markov Decision Problems