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This paper investigates consensus control in heterogeneous and uncertain multiple autonomous underwater vehicle (AUV) systems under implicit reduced visibility conditions. We address challenges such as environmental uncertainties and system nonlinearity by utilizing a unified connectivity approach to model low-visibility interactions and heterogeneous multi-AUV dynamics. Our main contributions include developing a feedback linearization model for heterogeneous multi-AUV systems that accounts for uncertainties, introducing an adaptive consensus controller based on relative positioning that effectively manages implicit visual interaction limitations and validating our strategies through stability analysis and numerical simulations. Our simulations demonstrate approximately a 60% improvement in accuracy compared to previous algorithms, highlighting the practical value of our approach in AUV recovery operations. These advancements provide a robust solution for consensus control in complex underwater environments.
Li et al. (Tue,) studied this question.