Lyapunov model predictive control to optimise computational burden, reference tracking and THD of three‐phase four‐leg inverter

Abstract

Due to the evolution of high processing microprocessors, the model predictive control (MPC) has been widely used in power electronic applications. In spite of simplicity, flexibility and fast dynamic response, the conventional MPC (C-MPC) has a drawback of computational burden. This study focuses on Lyapunov MPC (L-MPC) method, in which Lyapunov control law is employed in the cost function to minimise the error between the desired control variables and the actual control variables of three-phase four-leg inverter to optimise the closed-loop system performance. The proposed control algorithm takes advantage of a predefined Lyapunov control law which minimises the required calculation time by the Lyapunov model equations just once in each control loop to predict the future variables. L-MPC technique improves the digital speed by 23.8% as compared to C-MPC. It reduces current tracking error and total harmonic distortion (THD) in the variation of inverter control parameters. The stability of the system is established through Lyapunov function with the help of backsteping control method. The LabVIEW field programmable gate array (FPGA) rapid prototyping controller is used to validate the proposed control method. The experimental results showed that the proposed system has better performance as compared to C-MPC.