Voltage source inverters are extensively used in the grid connection of renewable energy-sourced generators, and multilevel converters, in particular, have attracted a great deal of attention in recent years. This paper investigates the application of a novel passivity-based sliding mode (PSM) control scheme on three-level grid-tie active Neutral-Point-Clamped (ANPC) inverters that yield fast and stable responses to grid impedance variations. Simulation studies confirm that this control scheme can produce high tracking performance and is also robust against grid load variations. Furthermore, to enhance ANPC efficiency, the loss distribution of switching devices controlled by the proposed strategy is evaluated. An optimal scheme is finally proposed for allocating silicon and Wide-Band-Gap switching devices, resulting in a hybrid ANPC inverter capable of achieving a desirable trade-off between the power losses and the device cost.

Sliding mode control (SMC) is widely used in permanent magnet linear synchronous motor (PMLSM) servo systems. However, improving the antidisturbance performance of SMC requires increasing the control gain, and excessive gain may induce severe sliding mode chattering. To resolve this trade-off, this manuscript proposes an adaptive high-order supercritical sliding mode control (AHOSSMC) method for PMLSM servo systems. By integrating high-order sliding mode control (HOSMC) with an adaptive gain strategy based on control barrier function (CBF), the conflict between disturbance rejection and chattering suppression is effectively mitigated, and the friction force in the PMLSM servo system is better compensated. Both the high-order sliding mode algorithm and the adaptive law are improved to enhance the performance of the AHOSSMC. Moreover, the switching behavior of the adaptive law is explicitly addressed to ensure continuous variation of the adaptive gain. Finally, comprehensive experimental validation is conducted to demonstrate the superior position tracking performance of the proposed AHOSSMC.