自然科学版 英文版
自然科学版 英文版
自然科学版 英文版

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中南大学学报(英文版)

Journal of Central South University

Vol. 27    No. 6    June 2020

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Three-dimensional neural network tracking control of autonomous underwater vehicles with input saturation
XU Rui-kun(徐瑞昆)1, TANG Guo-yuan(唐国元)1, 2, XIE De(解德)1, 2, HAN Li-jun(韩丽君)1

1. School of Naval Architecture and Ocean Engineering, Huazhong University of Science and Technology,Wuhan 430074, China;
2. Collaborative Innovation Center for Advanced Ship and Deep-Sea Exploration (CISSE),Shanghai 200240, China

Abstract:This paper addresses the problem of three-dimensional trajectory tracking control for underactuated autonomous underwater vehicles in the presence of parametric uncertainties, environmental disturbances and input saturation. First, a virtual guidance control strategy is established on the basis of tracking error kinematics, which resolves the overall control system into two cascade subsystems. Then, a first-order sliding mode differentiator is introduced in the derivation to avoid tedious analytic calculation, and a Gaussian error function-based continuous differentiable symmetric saturation model is explored to tackle the issue of input saturation. Combined with backstepping design techniques, the neural network control method and an adaptive control approach are used to estimate composite items of the unknown uncertainty and approximation errors. Meanwhile, Lyapunov-based stability analysis guarantees that control error signals of the closed-loop system are uniformly ultimately bounded. Finally, simulation studies are conducted for the trajectory tracking of a moving target and a spiral line to validate the effectiveness of the proposed controller.

 

Key words: autonomous underwater vehicles; trajectory tracking; neural networks; backstepping; input saturation

中南大学学报(自然科学版)
  ISSN 1672-7207
CN 43-1426/N
ZDXZAC
中南大学学报(英文版)
  ISSN 2095-2899
CN 43-1516/TB
JCSTFT
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