Abstract
This paper addresses the problem of control design for a nonlinear maneuvering model of an autonomous underwater vehicle. The control algorithm is based on an iteration technique that approximates the original nonlinear model by a sequence of linear time-varying equations equivalent to the original nonlinear problem and a self-tuning control method so that the controller is designed at each time point on the interval for trajectory tracking and heading angle control. This work makes use of self-tuning minimum variance principles. The benefit of this approach is that the nonlinearities and couplings of the system are preserved, unlike in the cases of control design based on linearized systems, reducing in this manner the uncertainty in the model and increasing the robustness of the controller. The simulations here presented use a torpedo-shaped underwater vehicle model and show the good performance of the controller and accurate tracking for certain maneuvering cases.
Highlights
The use of underwater vehicles has grown to a great extent over the last few decades [1].The so-called unmanned underwater vehicles (UUVs) and the autonomous underwater vehicles (AUVs) are of paramount importance in applications and procedures for underwater exploration, inspection, and maintenance of offshore structures
This paper addresses the problem of control design for a nonlinear maneuvering model of an autonomous underwater vehicle
The control algorithm is based on an iteration technique that approximates the original nonlinear model by a sequence of linear time-varying equations equivalent to the original nonlinear problem and a self-tuning control method so that the controller is designed at each time point on the interval for trajectory tracking and heading angle control
Summary
The use of underwater vehicles has grown to a great extent over the last few decades [1].The so-called unmanned underwater vehicles (UUVs) and the autonomous underwater vehicles (AUVs) are of paramount importance in applications and procedures for underwater exploration, inspection, and maintenance of offshore structures. In underwater vehicle autopilot design, the existing literature ranges from the application of PID and classical control [3] techniques to the application of modern techniques such as H-infinite [4], sliding model control [5,6,7,8,9,10], fuzzy control [11,12,13,14], neural networks [15], output feedback [16], linearization via state feedback [17], adaptive control [18], predictive control [19,20], and backstepping control [21,22] These control methods provide good results in the cited references but are—in most cases—restricted to a certain operational condition. A nonlinear generalized minimum variance (NGMV) methodology has been used in order to achieve a reduction in roll dynamics and the course-keeping motion in waves of ships [27,28], where a decoupled linear model for the application of the method was considered
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