Observer-Based Adaptive Sliding Mode Control of NPC Converters: An RBF Neural Network Approach

摘要

This paper proposes a novel control strategy for three-level neutral-point-clamped (NPC) power converter. The proposed control scheme consists of three control loops, i.e., instantaneous power tracking control loop, voltage regulation loop, and voltage balancing loop. First, in the power tracking control loop, a set of adaptive sliding mode controllers are established to drive the active and reactive power tracking to their desired values via radial basis function neural network technology. In the voltage regulation loop, an efficient but simple adaptive controller is designed to regulate dc-link output voltage where the load is considered as an external disturbance. Moreover, a composite controller is developed in the voltage balancing loop to ensure imbalance voltages between two dc-link capacitors close to zero, in which a reduced-order observer is used to estimate sinusoidal disturbance improving the converter performance. The effectiveness and superiority of the proposed control strategy for the NPC power converter are compared with other control schemes through experimental results.