Neural network control of a shunt active filter in MATLAB involves utilizing artificial neural networks (ANNs) to enhance the performance of the shunt active filter in mitigating harmonic distortions and improving power quality in electrical systems. The process entails modeling the shunt active filter and training a neural network to effectively regulate the filter's operation based on real-time measurements of the system's voltage and current waveforms. By employing ANN-based control strategies, the shunt active filter can adaptively adjust its compensation signals to dynamically suppress harmonics and reactive power, thereby improving overall system stability and efficiency. MATLAB provides a flexible platform for implementing neural network control algorithms, allowing for the development, simulation, and optimization of shunt active filter control strategies tailored to specific grid conditions and harmonic profiles. This approach offers a promising avenue for enhancing the performance of shunt active filters in mitigating power quality issues in electrical networks.