Now-a-days, model predictive control (MPC) is very commonly used for three phase inverters. But conventional MPC suffers computational complexities as well as unstable switching frequency issues. To address these issues related with conventional MPC model, this paper aims to use the benefits of deep learning model for predictive switching control. In this paper, CNN-LSTM network based predictive control is proposed for three phase inverters. Along with predictive control LC filter is cascaded to reduce the harmonics. The model is simulated using SIMULINK under fixed and dynamic load condition. The result shows decreased THD under different load conditions. Finally, the result is validated with existing models and achieves better performance
