Adaptive Intelligent Super-Twisting Control of Dynamic System

This study develops an adaptive Super-Twisting sliding mode control (STSMC) approach using an output feedback fuzzy neural network (OFFNN) for dynamic systems. The OFFNN approximator is designed to approach the model uncertainty, and a signal feedback loop could provide better data learning capabilities and more reasonable learning rate, therefore the proposed controller has full regulation and high approximation accuracy. Real-time experimental studies of an active power filter are accomplished to show the proposed controller has better harmonic suppression and steady-state and dynamic property than existing methods.

Automated summary

This study presents an adaptive Super-Twisting sliding mode control approach using an output feedback fuzzy neural network for dynamic systems. Experimental results demonstrate that the proposed controller achieves better harmonic suppression and steady-state and dynamic properties.