Adaptive control of power factor correction converter using nonlinear system identification

PID controllers have been very successful in industrial applications. However, for nonlinear processes, their performances are not very satisfactory. Conventional active power factor correction (PFC) converters use classical PI controllers to carry out output voltage regulation and power factor correction. Since the process is highly nonlinear, an adaptive controller has been developed to improve the performance of PFC converters. An orthogonal least squares estimation algorithm was incorporated for the identification of boost converters. A parsimonious nonlinear model for power converters was obtained based on the output prediction and the error reduction ratio test. The least mean squares algorithm is then implemented for the online tracking of the system parameters and the adaptive controller was derived based on the fitted model. Experimental studies were carried out to demonstrate the effectiveness of the proposed identification and control algorithm for power factor correction and harmonic elimination.