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| Title: | Adaptive control for autonomous ships with uncertain model and unknown propeller dynamics | | | Authors: | A. Haseltalab, R.R. Negenborn |
| | Journal: | Control Engineering Practice | | |
| | Abstract: | Motion control is one of the most critical aspects in the design of autonomousships. During maneuvering, the dynamics of propellers as well as the craft hy-drodynamical specifications experience sever uncertainties. In this paper, anadaptive control approach is proposed to control the motion and trajectorytracking of an autonomous vessel by adopting neural networks that is used forestimating the dynamics of the propellers and handling hydrodynamical uncer-tainties. Considering that the maneuvering model of a vessel resemble a non-linear non-affine-in-control system, the proposed neural-based adaptive controlalgorithm is designed to estimate the nonlinear influence of the input functionwhich in this case is the dynamics of propellers and thrusters. It is also shownthat the proposed methodology is capable of handling state dependent uncer-tainties within the ship maneuvering model. A Lyapunov-based technique andUniform Ultimate Boundedness are used to prove the correctness of the algo-rithm. To assess the method's performance, several experiments are consideredincluding trajectory tracking simulations in the port of Rotterdam. |
| | Reference: | Adaptive control for autonomous ships with uncertain model and unknown propeller dynamics. A. Haseltalab, R.R. Negenborn. Control Engineering Practice, vol. 91, no. 104116, October 2019. | | | Request: | A
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