A Fuzzy-adaptive sliding mode control strategy for optimizing control of underwater drone

Abstract

Controlling underwater robots with nonlinear dynamics is a challenging task. Sliding Mode Control (SMC), a widely used framework for underwater vehicles, suffers from chattering effects that degrade performance. Despite this drawback, SMC remains popular due to its inherent robustness against model uncertainties and external disturbances—an essential requirement in the unpredictable underwater environment. This study proposes a Type-1 fuzzy-adaptive SMC to mitigate this issue, where fuzzy logic dynamically tunes SMC parameters for smoother operation. The method significantly reduces chattering in the baseline SMC model while preserving its robustness. The proposed approach is implemented and validated in the Gazebo simulation platform. This control strategy enhances user experience and vehicle longevity by minimizing high-frequency oscillations, offering practical benefits for remotely operated systems.