Design of Adaptive Control and Fuzzy Neural Network Control for Single-Stage Boost Inverter

This study mainly focuses on the development of two newly designed control strategies including an adaptive control scheme and a fuzzy neural network (FNN) control system for a single-stage boost inverter. First, the dynamic model of a single-stage boost inverter is analyzed and built for the later control manipulation. Then, a model-based adaptive control scheme and a model-free FNN control system with varied learning rates are designed sequentially. The effectiveness of the proposed adaptive control scheme and the proposed FNN control system is verified by experimental results of a 1-kW single-stage boost inverter prototype, and their merits are indicated in comparison with a traditional double-loop proportional-integral (PI) control framework. Experimental results show that the superior FNN control system has significant improvements of 45.2% total harmonic distortion and 37.1% normalized mean square error compared to the conventional double-loop PI control framework under nonlinear loads.