Continuous Control-Set Model-Predictive Control with stability guarantee for the PWM-VSC

The presence of power electronics converters has become more and more dominant in power systems and this is posing stricter requirements for their controls in terms of stability and performance. The class of Model Predictive Controls (MPC) is particularly well suited for power electronics converters for its inherent ability to incorporate constraints while ensuring high dynamic performance. However, conventional approaches to guarantee stability may complicate the optimal control problem to the extent of making it unrealizable. This paper presents a Continuous Control-Set Model Predictive Control (CCS-MPC) for the Pulse-Width Modulated Voltage Source Converters (PWM-VSC). The bilinear structure of the discrete-time dynamic model is used to obtain a convex optimization problem that ensures a unique and global optimum solution in each step. Moreover, the stability is guaranteed via a discrete-time Lyapunov function derived directly from the Karush–Kuhn–Tucker (KKT) conditions. The proposed control shows a simple implementation with remarkable stability, performance, and clear advantages over the conventional design approach. These properties have been validated both in numerical simulations and experimentally on a 60 kVA converter. • A continuous-control-set MPC is proposed for the voltage-source converters. • The optimal control problem is convex and guarantees global optimum. • Constraints are integrated into the model via Karush–Kuhn–Tucker conditions. • Stability is guaranteed via a quadratic Lyapunov function. • Simulation and experimental results demonstrate the high performance of the control.