Model Predictive Control Based PID Controller for PMSM for Propulsion Systems

Model Predictive Control (MPC) is one of the most suitable controllers for industrial applications, especially for constrained systems. However, it requires high computational burden, which is considered as the main drawback. Proportional Integral Derivative (PID) controller is the most widely used controller in particular for Single Input Single Output (SISO) system and for cascaded control loops, but it is difficult to be tuned especially for a constrained system. Therefore, a combination of PID and MPC is addressed. The basic concept of the proposed technique concentrates on the tuning of PID controller gains based on the MPC performance for the closed loop system considering constraints, which will be applied in a control system consisting of two hierarchical levels structure. The algorithm is applied to control the speed of Permanent Magnet Synchronous Motor (PMSM), which is considered as Multi Input Multi Output (MIMO) system.

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