期刊
OCEAN ENGINEERING
卷 218, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.oceaneng.2020.108193
关键词
Trajectory tracking; Under-actuated AUV; Adaptive neural network control; Asymmetrical actuator saturation; Approach angle
资金
- National Natural Science Foundation of China [52071153]
- Shenzhen Science and Technology Plan Project [JCYJ201704I311305468]
- Fundamental Research Funds for the Central Universities [2017KFYXJJ005, 2019JYCXJJ005]
- State Key Lab Research Fund of Ocean Engineering [201504]
In this paper neural-network (NN) based adaptive trajectory tracking control scheme has been designed for underactuated Autonomous Underwater Vehicles (AUVs) which are subjected to unknown asymmetrical actuator saturation and unknown dynamics. First, some control preliminaries and assumptions along with AUV kinematic & kinetic models and trajectory tracking problems are elaborated. Secondly, the tracking error model and tracking guidance law are derived based on the theory of relative motion and the principle of approach angle respectively. Then the kinematic controller is designed by using the backstepping technique and Lyapunov theory. Similarly, AUV kinetic controller is designed by using the NN compensation and adaptive estimation techniques which is termed as NN-based adaptive controller (NNAC). Pertinently, a novel bounded saturation function has been developed to describe the unknown asymmetrical actuator saturation. The NN is adopted to approximate the complex AUV hydrodynamics and differential of desired tracking velocities. The bound of the generalized disturbance, which is composed of NN approximation error and ocean disturbances, are approximated based on the adaptive estimation technique. To analyze the stability of the developed NNAC, Lyapunov theory and backstepping technique are utilized by considering the control actions on different saturation sections. Finally, effectiveness and superiority of the proposed NNAC are validated through two sets of comparative simulation studies.
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