Optimized PI Gain in UPQC Control Based on Improved Zero Attracting Normalized LMS

Abstract

An Improved Reweighted Zero Attracting Normalized Least Mean Square (IRZA-NLMS) based control scheme is applied in 4-wire Unified Power Quality Conditioner (UPQC) to mitigate current and voltage-based power quality issues. The IRZA-NLMS algorithm has increased efficiency with regard to exploratory rate, steady-state error, and overcoming the drawbacks of NLMS techniques. To raise convergence rate of active signals, the IRZA-NLMS algorithm uses an efficient threshold-based gain function and involvement of zero attracting term is used to determine the inactive signals to their optimum zero stage. In addition to IRZA-NLMS algorithm, a Self-Adaptive Multi Population Rao (SAMP-Rao) optimization is employed to evolve gains of the proportional integral (PI) controller. The SAMP- Rao increases diversity of solution search by splitting total considered population into sub-population groups, each of which searches for the optimal solution in a search space, ensuring that no single individual is trapped in a local minima and allowing for better exploration and exploitation search. The Integral Time Absolute Error objective function is used to optimize the gains of PI controller of DC and AC link voltage. In laboratory environment, the prescribed method is implemented through Micro-lab box processor with MATLAB interface.