Journal
IEEE TRANSACTIONS ON CYBERNETICS
Volume 52, Issue 8, Pages 7453-7463Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCYB.2020.3041368
Keywords
Performance analysis; Trajectory; Hydrodynamics; Sea surface; Backstepping; Uncertainty; Optimal control; Auxiliary system; learning and near-optimal control (LNOC); mismatched periodic disturbances; underactuated surface (USV) vessel
Categories
Funding
- Fundamental Research Funds for the Central Universities [21620346]
- National Natural Science Foundation of China [61932011, 61825203, U1736203, 61732021]
- Major Program of Guangdong Basic and Applied Research Project [2019B030302008]
- Guangdong Provincal Science and Technology Project [2017B010111005]
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This article presents a novel learning and near-optimal control approach for underactuated surface vessels with unknown disturbances and hydrodynamic parameters, where an analytical near-optimal control law is derived and state differences between auxiliary and controlled systems are proven to converge to zero globally. The method theoretically guarantees the asymptotic optimality of the performance index, as demonstrated through simulations based on real parameters of USV vessels.
In this article, we propose a novel learning and near-optimal control approach for underactuated surface (USV) vessels with unknown mismatched periodic external disturbances and unknown hydrodynamic parameters. Given a prior knowledge of the periods of the disturbances, an analytical near-optimal control law is derived through the approximation of the integral-type quadratic performance index with respect to the tracking error, where the equivalent unknown parameters are generated online by an auxiliary system that can learn the dynamics of the controlled system. It is proved that the state differences between the auxiliary system and the corresponding controlled USV vessel are globally asymptotically convergent to zero. Besides, the approach theoretically guarantees asymptotic optimality of the performance index. The efficacy of the method is demonstrated via simulations based on the real parameters of an USV vessel.
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