Data-driven Degradation-Aware Model Predictive Control for Power Electronics

With the development of artificial intelligence, the control strategies for critical power devices has a diversity such that more reliability solution can be guaranteed in diversity complicated working condition. LC-inverter is known as one of the most applied power conversion equipment nowadays due to the significantly increasing demand for more electrical transportation and multiple renewable energy source generation. To address the challenge of developing a degradation-aware control strategy, this paper intend to incorporates a novel degradation to the finite-set model predictive control for the LC inverter.