## 1 Introduction  
Shunt active power filter (SAPF) is a well-recognized power electronics tool applied for mitigating harmonic currents sourced by non-linear harmonic producing loads. Its purpose is to recover sinusoidal shape and balanced property of source currents by injecting equal amount of harmonic currents in opposite phase (referred here as injection currents) to the existing harmonic currents retained in the power system. In modern days, installation of SAPF has been made compulsory due to increasing penetration of power electronics devices into power systems where they have significantly contaminated the power system with harmonic currents. SAPFs are revealed to be flexible and adaptive where they can favorably be installed in any harmonic-contaminated power systems [1]. These are the key features of SAPFs that allow them to overcome the main limitations of traditional tuned filters which are passive and non-adaptive (fixed filtering feature), and eventually grabbed the status as the best harmonic currents solution [2]. However, the developing innovative approaches that allow SAPFs to perform at the peak of their ability have always remained a core challenge. In this regard, progressive research works have been performed extensively to investigate and subsequently improve performance of SAPF by developing new control techniques. Generally, to manage operation of SAPF, three distinct groups of control algorithm need to be integrated in its controller: (1) harmonics extraction, (2) dc-link voltage regulation, and (3) current control algorithms [3; 4]. Among the three control categories, harmonics extraction algorithms are acknowledged to be most essential because they hold the responsibility to provide the controller with reference current signal. It is worth noting that reference current signal is the main signal that guides the generation of control signals and eventually the operation of SAPF. Hence, without having an accurate reference signal as guideline, there is no way the SAPF can perform as desired. A few popular techniques for developing harmonics extraction algorithms include synchronous reference frame (SRF) [5; 6], instantaneous power (PQ) theory [7; 8], Fourier transform [9; 10], and artificial neural network (ANN) [11; 12] techniques. Among the aforementioned techniques, harmonics extraction developed based on ANN or more specifically adaptive linear neuron (ADALINE) concept, is most reliable in providing accurate estimation of reference current [13]. In operation, ADALINE-based approaches are technically managed by a modified Widrow-Hoff (W-H) weights updating algorithm [11; 14] which matches an estimated signal to an actual signal by continuously updating the weights of each neuron (sine and cosine components). In the context of SAPF applications, an early work on ADALINE-based harmonics extraction algorithm was performed on single-phase systems [11] where it was reported to effectively manage the operation of SAPF under ideal source voltage and steady state conditions. The work has been further improved as fundamental active current (FAC)-ADALINE where it allows the controlled SAPF to work effectively under dynamic state conditions [13]. Further progressive works have been performed to expand the application of ADALINE-based approaches to address harmonic problems in three-phase three-wire systems [15; 16]. For three-phase applications, the single-phase ADALINE technique can be adopted directly, i.e., by assigning similar single-phase ADALINE module across each phase of the three-phase networks. In this manner, the design efforts can particularly be reduced as similar design requirements are applied for each phase (modular structure). Performances of ADALINE-based approaches in three-phase three-wire systems have been verified (both simulation and experimentally) under sinusoidal source, balanced load, and dynamic state scenarios [16].