4.7 Article

Adaptive dynamic surface control for cooperative path following of marine surface vehicles with input saturation

期刊

NONLINEAR DYNAMICS
卷 77, 期 1-2, 页码 107-117

出版社

SPRINGER
DOI: 10.1007/s11071-014-1277-5

关键词

Cooperative path following; Dynamic surface control; Marine surface vehicles; Neural networks; Input saturation

资金

  1. National Nature Science Foundation of China [61273137, 51209026, 61074017]
  2. Scientific Research Fund of Liaoning Provincial Education Department [L2013202]
  3. Fundamental Research Funds for the Central Universities [3132013037, 3132014047]

向作者/读者索取更多资源

This paper considers the cooperative path following problem of multiple marine surface vehicles subject to input saturation, unknown dynamical uncertainty and unstructured ocean disturbances, and partial knowledge of the reference velocity. The control design is categorized into two envelopes. Path following for each vehicle amounts to reducing an appropriately defined geometric error. Vehicles coordination is achieved by exchanging the path variables, as determined by the communications topology adopted. The control design is developed with the aid of the neural network-based dynamic surface control (DSC) technique, an auxiliary design, and a distributed estimator. The key features of the developed controllers are as follows. First, the neural network-based adaptive DSC technique allows for handling the unknown dynamical uncertainty and ocean disturbances without the need for explicit knowledge of the model, and at the same time simplify the cooperative path following controllers by introducing the first-order filters. Second, input saturations are incorporated into the cooperative path following design, and the stability of the modified control solution is verified. Third, the amount of communications is reduced effectively due to the distributed speed estimator, which means the global knowledge of the reference speed is relaxed. Under the proposed controllers, all signals in the closed-loop system are guaranteed to be uniformly ultimately bounded. Simulation results validate the performance and robustness improvement of the proposed strategy.

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