MIMO control systems offer a powerful approach to handling complex control problems with multiple inputs and outputs. They provide increased flexibility, improved performance, and better system behavior compared to SISO systems, making them an essential tool in modern control engineering.
System identification is a field of study in control engineering that focuses on the process of determining mathematical models or descriptions of dynamic systems based on observed input-output data. The goal of system identification is to extract information about the underlying system dynamics, such as the transfer function, state-space representation, or other mathematical models that accurately capture the system’s behavior.
MPC is a model-based control strategy that relies on an accurate mathematical model of the system to make predictions and optimize control actions over a finite time horizon. MPC is particularly effective in situations where there are constraints on the system outputs, inputs, or states.
The power of game theory at modeling a wide variety of situations such as Simultaneous games, Sequential games, Cooperative games, Non-cooperative games, Static games, Dynamic games, Stochastic games, etc, made it applicable to different fields of science like Engineering, Politics, Economics and Computer Science.
