A chattering-free sliding-mode controller for underwater vehicles with fault-tolerant infinity-norm thrust allocation

There are two objectives to this paper. First, a chattering-free sliding-mode controller is proposed for the trajectory control of remotely operated vehicles (ROVs). Second, a new approach for thrust allocation is proposed that is based on minimizing the largest individual component of the thrust manifold. With regards to the former, a new adaptive term is developed that eliminates the high-frequency control action inherent in a conventional sliding-mode controller. As opposed to the common adaptive approach, the new adaptive term does not require the linearity condition on the dynamic parameters and the creation of a regressor matrix. In addition, it removes the need for a priori knowledge of upper bounds on uncertainties in the dynamic parameters of the ROV. With regards to the latter, it is demonstrated that minimizing the l∞ norm (infinity-norm) of the thrust manifold ensures low individual thruster forces. The new control and thrust allocation concepts are implemented in numerical simulations of a work class ROV, and the chattering-free nature of the controller is demonstrated during typical ROV manoeuvres. In the simulation studies, the l∞ norm-based thrust allocation problem is cast as a linear programming problem that allows direct incorporation of the thruster saturation limits and a fault-tolerant property. To achieve real-time solution rates for the l∞ norm-based thrust allocation problem, a recurrent neural network is designed. In the simulation studies, the l∞ norm-based thrust allocation provides smaller maximum absolute value of the largest component of the thrust manifold than that of a conventional l2 norm (2-norm) minimization, satisfies the saturation limits of each thruster, and accommodates faults that are introduced arbitrarily during the manoeuvre.