Model Predictive Control in Mechatronic, Robotic, and Networked Systems

Dear Colleagues,

Model predictive control (MPC) is a control design methodology that appeared at the beginning of the 80s through which an open-loop finite-horizon optimization problem with embedded constraints is solved at each time-step based on the receding horizon principle. This principle involves the application of the first value from the computed control sequence, and, at the next time-step, the system state is measured/estimated and the optimal control sequence is re-computed.

MPC has received increasing interest among researchers and control practitioners in industries. The predictive control strategies were initially utilized for slow processes, e.g., oil refineries, petrochemicals, pulp and paper, primary metal industries, and gas plants. Starting with the evolution of hardware components and algorithms, the possibility to implement these types of control algorithms to fast processes with reduced sampling periods, appeared, e.g., mechatronics, automotive control, aero-spatial applications, autonomous robotics, power generation, and distribution.

Predictive control techniques have been introduced mainly in order to deal with plants that have complex dynamics (unstable inverse systems, time-varying delay, etc.) and plant model mismatch. They are of particular interest from the point of view of both broad applicability and implementation simplicity, being applied on a large scale in industry processes, with good performances and being robust at the same time.

Contributions from all fields related to Model Predictive Control in Mechatronic, Robotic, and Networked Systems are welcome to this Special Issue, including, particularly, the following:

• Decentralized, hierarchical, and distributed MPC
• Large-scale and cloud-based MPC
• MPC for cyber-physical systems
• Artificial intelligence in MPC
• Real-time implementation of MPC
• Applications of MPC in servo drives and electrical power drives
• Applications of MPC in industrial and mobile robotics
• Applications of MPC in industrial process control
• Applications of MPC in automotive systems
• Applications of MPC in networked and distributed systems

Prof. Dr. Constantin Caruntu
Dr. Cosmin Copot
Guest Editors

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