Indirect Model Predictive Control for Capacitor Energy Control in Modular Multilevel Converters

Model predictive control (MPC) has emerged as a promising approach for the control of systems with complex, non-linear dynamics, such as modular multilevel converters (MMCs). However, despite the intrinsic nonlinear nature of MMCs, linear MPC is predominantly applied, often without a thorough analysis of how the nonlinearities of the MMC affect control performance and constraint compliance. This paper identifies the impact of the MMC nonlinearities on the control performance of linear MPC and proposes a cascaded approach to mitigate their effects. The proposed approach ensures that the system constraints are still met when linear MPC is applied to the nonlinear MMC. The performance of the cascaded MPC strategy is validated by high-fidelity MATLAB/Simulink simulations and compared to state-of-the-art MPC implementations.