Inverse Model Predictive Control for Power Electronic Converters

In this paper, a new control technique called inverse model predictive control (IMPC) is proposed for power electronic converters. The proposed IMPC technique is primarily based on the inverse of the conventional finite set model predictive control. The key advantage of this design is that it avoids predicting the controlled states for all possible switching-state vectors, while maintaining the advantage of adhering to multiple constraints and achieving multiple objectives. IMPC predicts the optimal control signal that minimizes the cost function and converts it into a switching vector. Unlike classical MPC, the computational time required for IMPC is significantly reduced which makes it easily applicable to all types and levels of power electronics converters. The proposed method does not depend on the number of possible switching vectors and is compatible with low-cost microcontrollers commonly used for industrial applications. Additionally, the proposed control inherits the benefits of MPC, such as the ability to achieve its objectives while adhering to various constraints, minimal parameters tuning requirements, and reduced computational time. To demonstrate the effectiveness of the proposed technique, experimental results are presented for a five-level active neutral point clamped flying capacitor inverter (ANPC-FC) as a case study.