Adaptive Sliding Mode Control With Chebyshev Neural Disturbance Observer for Active Power Filter

For the purposed of mitigating harmonics caused by power electronic devices, a novel adaptive sliding mode control (NASMC) strategy utilizing a Chebyshev neural disturbance observer (CNDO) is introduced for controlling an active power filter (APF). By adopting a novel adaptive law, NASMC scheme effectively achieves superior tracking performance while minimizing the impact of chattering, where the arbitrarily small vicinity of sliding manifold is taken into consideration and the derivative of switching gain is divided into three states. Such adaptive law enables extraordinary ability to rapidly adapt and effectively reduce the emergence of chattering and singularity in close proximity to the sliding manifold. Moreover, an adaptive recursive Chebyshev fuzzy neural network (ARCFNN) has been integrated into the disturbance observer to alleviate the dependence on APF parameters. Concurrently, the CNDO can accurately estimate and compensate for inherent modelling nondeterminacy and exterior perturbation within the APF system, thus reducing the vibrating and reinforcing overall system robustness. The proposed control scheme has been effectively validated through a series of simulations and experiments, demonstrating superior performance over other methods.