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

The unique advantages of modular multilevel converters (MMCs) have led to wide adoption
of the converter topology in high voltage dc (HVDC) transmission systems, with great …

The integration of artificial intelligence (AI) techniques in power converter-based systems
has the potential to revolutionize the way these systems are optimized and controlled. With …

Parameter design is significant in ensuring a satisfactory holistic performance of power
converters. Generally, circuit parameter design for power converters consists of two …

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 …

Power converters and motor drives are playing a significant role in the transition towards
sustainable energy systems and transportation electrification. In this context, rich diversity of …

This article introduces the control and operation of a grid-connected converter with an
energy storage system. A complete mathematical model was presented for the developed …

Model-predictive control is a constrained optimization control method with superior
performance than linear methods for multivariable and multiobjective control of power …

In this article, a novel robust data-driven model-free predictive control framework based on
the I/O data of the controlled plants, which is performed by incorporating the neural predictor …

In this literature, we concentrate on investigating a learning-based resilient predictive control
framework using variable-step event-triggered mechanism, which aims to avoid …