Object manipulation by collaborative autonomous underwater vehicles driven by a model-free second-order sliding mode controller with finite-time convergence
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Abstract
The use of Autonomous Underwater Vehicles (AUV) has expanded in recent years to include them in inspection, maintenance, and repair missions. These missions require the automation of tasks such as autonomous navigation and station-keeping, which are pretty challenging due to the complexity of the vehicle itself and the underwater environment. Traditional control strategies have been used to deal with those problems before, but their performance is limited since they do not consider non-linearities, external disturbances, or model uncertainties. Non-traditional controllers have been explored too, but have shortcomings such as being model-based, parameter-dependant, or so. Additionally, the nature of some objects implies the involvement of multiple vehicles to manipulate them, making the manipulation mission even harder. Collaboration of AUVs is a strong challenge since underwater communications are limited or null. An advanced control strategy dealing with the trajectory tracking and the station-keeping problem would be desirable for simplicity and robustness. If this controller could also help coordinate multiple vehicles without requiring them to communicate with each other, it would make collaborative manipulation tasks reachable. For this purpose, a model-free high-order Sliding Mode Controller (SMC) is presented in this project. Unlike other control approaches, the proposed control strategy achieves finite-time convergence to a practical zero error in a time-base that the user can arbitrarily define. This characteristic will be used to coordinate the navigation of two AUVs to manipulate an object underwater. The performance of the proposed controller was evaluated by numerical simulations and experiments in a semi-Olympic swimming pool and compared with classic and state-of-the-art control strategies regarding trajectory tracking and station-keeping problems. Results have shown that the proposed controller can achieve finite-time convergence of the tracking errors to a practical zero value in the predefined time-base. Results also demonstrated that the convergence time could be arbitrarily selected by the user and achieved by the controller resulting in, as far as the author knows, the first controller with this characteristic for AUVs navigation. The simulations and experiments also showed that the proposed controller outperformed classical and state-of-the-art controllers regarding the Root Mean Square of the tracking errors and energy consumption. Finally, the proposed model-free high-order SMC coordinated two BlueROV2 vehicles in a collaborative manipulation mission without vehicle-to-vehicle communication. Numerical simulation results confirmed that the proposed controller could manage the vehicles to follow a predefined coordinated trajectory to approach, grip, transport, and release an object without communicating with each other.