Abstract
The article portrays an adaptive control paradigm for the swift response of a solid-oxide fuel cell (SOFC) in a grid-connected microgrid. The control scheme is based on an adaptive feedback-linearization-embedded fully recurrent NeuroFuzzy Laguerre wavelet control (FBL-FRNF-Lag-WC) framework. The nonlinear functions of feedback linearization (FBL) are estimated using a fully recurrent NeuroFuzzy Laguerre wavelet control (FRNF-Lag-WC) architecture with a recurrent Gaussian membership function in the antecedent part and a recurrent Laguerre wavelet in the consequent part, respectively. The performance of the proposed control scheme is validated for various stability, quality, and reliability factors obtained through a simulation testbed implemented in MATLAB/Simulink. The proposed scheme is compared against adaptive NeuroFuzzy, PID, and adaptive PID (aPID) control schemes using different performance parameters for a grid-connected load over 24 h.
Highlights
The growing population of the world demands more and more energy to fulfill its daily routine
The performance of the proposed adaptive feedback linearization (FBL)-FRNF-Lag-WC is verified against the conventional PID and adaptive PID (aPID) control schemes, and the results are shown for various parameters
The variations in the net AC bus power produced by the adaptive NeuroFuzzy and by the conventional control schemes were of higher magnitude than that of the adaptive FBL-FRNF-Lag-WC
Summary
The growing population of the world demands more and more energy to fulfill its daily routine. The limited supplies of conventional energy resources will reach their end one day, which affects every sector of life on the globe. Li et al [15] provided a hierarchical load-tracking control for an SOFC connected to a grid, but the scheme was restricted to its constraints, as mentioned in the article. Mumtaz et al [4] and Mumtaz and Khan [13] proposed advanced control techniques using a Hermite wavelet incorporated into a NeuroFuzzy indirect adaptive control scheme for the control problem of SOFCs. This article presents a novel adaptive feedback-linearization-embedded fully recurrent. NeuroFuzzy Laguerre wavelet control (FBL-FRNF-Lag-WC) technique for the control of SOFCs integrated into a microgrid. The unknown functions of feedback linearization (FBL) control are estimated using fully recurrent NeuroFuzzy Laguerre wavelet control (FRNF-LagWC).
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