As the smart grid evolves, it requires increasing distributed intelligence, optimization and
control. Model predictive control (MPC) facilitates these functionalities for smart grid …

Model-predictive control (MPC) has emerged as a promising control method in power
electronics, particularly for multiobjective control problems such as multilevel inverter (MLI) …

The application of model predictive control in electrical drives has been studied extensively
in the past decade. This article presents what the authors consider the most relevant …

There is a trend to use artificial neural networks (ANNs) as approximation models to
implement explicit model-predictive control (EMPC) on hardware. However, the vanilla ANN …

In this article a finite control set model predictive control, is used to track a current reference
in a power converter connected to an load. An artificial intelligence approach is presented …

Artificial neural network (ANN) has recently been considered in weighting factors (WFs)
optimization for finite control-set model predictive control (FCS-MPC). However, the training …

An improved particle swarm optimization (PSO) algorithm based on Gaussian distribution
model is proposed to realize the autotuning of weighting factors for the cost function design …

This letter concentrates on introducing a learning methodology that extends and improves
classical finite control-set model predictive control approach, which is able to significantly …

Finite control set model predictive control (FCS-MPC) is a salient control method for power
conversion systems that has recently enjoyed remarkable popularity. Several studies …

Model predictive control (MPC) has become one of the most attractive control techniques
due to its outstanding dynamic performance for permanent magnet synchronous motor …