Lyapunov-based finite control-set model predictive control for nested neutral point-clamped converters without weighting factors

Abstract

This paper presents a novel finite control-set model predictive control (FCS-MPC) strategy for solving the well-known challenges in predictive control regulated NNPCs, which aims to avoid the tedious online adjustment of weighting factors and to achieve the flexible power regulation. Firstly, a modified cost function, which is inspired by Lyapunov control theory, is formulated from system stability point of view. As such, the designed Lyapunov-based cost function has a good potential to avoid the selection of weighting factors for the conventional FCS-MPC scheme, especially in the presence of multiple control objectives. Next, in order to achieve satisfactory regulation performance, a dynamic reference design technique is introduced as an alternative solution to serve this purpose. Worth to note that the computational complexity will be increased while applying the proposed design methodology to the control of NNPCs. In this sense, a computationally efficient FCS-MPC strategy based on Lyapunov theory is presented here. Therefore, the overall computational burden is significantly decreased while maintaining fast transient performance and flying capacitor voltages balancing. Finally, compared with the state-of-the-art FCS-MPC strategies, the effectiveness and feasibility of the proposed methodology for NNPCs are confirmed through comprehensive simulation and experimental results.