Framework for fair comparisons of underwater vehicle controllers - showcasing the robustness properties of a model-free sliding mode controller tuned with a random-forest-based Bayesian optimization approach

Marcusso Manhães, Musa MorenaMusa MorenaMarcusso ManhãesScherer, Sebastian A.Sebastian A.SchererDouat, Luiz RicardoLuiz RicardoDouatVoss, MartinMartinVossRauschenbach, ThomasThomasRauschenbach2022-03-132022-03-132017https://publica.fraunhofer.de/handle/publica/39870110.5220/0006427001020113Tasks with underwater vehicles present several challenges that include complex and hazardous environments, and unmodeled and/or unknown uncertainties. The setup of positioning controllers is therefore a difficult and laborious task and very often leads to suboptimal performance results on the field. This paper shows a framework for methodical evaluation and setup of dynamic positioning controllers for underwater vehicles with simulation-based optimization method using performance metrics. The proposed method can be configured to be mission specific and delivers a controller configuration that also allows a fair numerical comparison between control algorithms on similar scenarios.enunderwater roboticrobust controlSMACsliding mode controlunderwater robotics simulationFramework for fair comparisons of underwater vehicle controllers - showcasing the robustness properties of a model-free sliding mode controller tuned with a random-forest-based Bayesian optimization approachconference paper