Model Predictive Control: Algorithms and Applications

Dear Colleagues,

Model predictive control (MPC) is an advanced control method which makes it possible to effectively control multivariable and nonlinear processes subject to constraints. MPC is not only an active area of research, but also has a great number of applications in different fields. MPC has been traditionally used in process control, but due to the availability of powerful microcontrollers, MPC algorithms have become increasingly popular in fast embedded systems, e.g., automotive applications, drones, quadcopters, and robots.

The aim of this Special Issue is to present state-of-the-art algorithms used in MPC and report interesting applications of MPC in different fields. The possible topics of interest include, but are not limited to, the following areas:

Algorithms

Control quality assessment of MPC
Data-driven MPC
Economic MPC
Embedded MPC
Hierarchical and decentralized MPC
IT solutions for MPC
Large-scale MPC
Learning MPC
MPC in IoT systems
Online learning in MPC
Optimization algorithms for MPC
Setpoint optimization in MPC
Stability and robustness of MPC
Stochastic MPC

Applications

Applications of MPC in automotive systems
Applications of MPC in energy systems
Applications of MPC in heating, ventilation, air conditioning (HVAC) systems
Applications of MPC in industrial process control

Dr. Maciej Ławryńczuk
Guest Editor

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