A Model-free Output Feedback Adaptive Optimal Fuzzy Controller for LC-filtered Three-phase Voltage Source Inverters

This paper proposes a model-free output feedback control-based adaptive fuzzy controller using a current-sensorless configuration for LC-filtered three-phase voltage source inverters (VSIs). The proposed adaptive fuzzy scheme is constructed of three parts: an adapter, an adaptive optimal fuzzy controller, and an adaptive optimal fuzzy identifier. The adapter is designed based on an adaptive neuro-fuzzy inference system (ANFIS) network which uses the error between the system output and identifier output as an input to generate the online updated parameters. Next, both the adaptive fuzzy controller and the fuzzy identifier are designed based on the Takagi-Sugeno (T-S) fuzzy model. In particular, the proposed algorithm is robust against external disturbance and parameter uncertainties due to not requiring the system parameters. Moreover, the proposed scheme uses a current-sensorless configuration, which reduces the system complexity and cost. Both the stability of the proposed method and the convergence of adapted parameters are completely assured by using the Lyapunov stability theory. Finally, the effectiveness of the proposed adaptive fuzzy controller is verified through simulation in comparison with a conventional T-S fuzzy controller. The results show that the proposed model-free output feedback control-based adaptive fuzzy controller yields better control performance, such as faster transient response, smaller steady-state error, and lower total harmonic distortion (THD) under the change of load (step changes of linear load, unbalanced load, and nonlinear load), parameter variations, and input disturbances.