输入约束下的浮力调节式UUV变深控制

doi:10.12305/j.issn.1001-506X.2022.11.25

Abstract

Abstract:

Aiming at the problem of variable depth control of unmanned underwater vehicle(UUV) constrained by the buoyancy regulator mechanism, an adaptive dynamic surface control method based on the orthogonal neural network saturation compensator is proposed. Firstly, the UUV mathematical model considering the dynamic characteristics of the actuator is established. On this basis, the dynamic surface controller is designed by using the backstepping method and the nonlinear tracking differentiator. The linear extended state observer (LESO) is designed to estimate the disturbance caused by buoyancy change and model uncertainty online. Then compensation is carried out in the controller. Secondly, the saturation compensator is designed based on the orthogonal neural network. It is proved that all the errors of the closed-loop system are consistent and finally bounded. The simulation results show that the proposed method has better dynamic performance and steady-state precision under the constraint of the buoyancy regulator mechanism compared with the existing dynamic surface control method.

Key words: buoyancy regulator, unmanned underwater vehicle (UUV), dynamic surface controller, linear extended state observer (LESO), orthogonal neural network saturation compensator

CLC Number:

TP273

Haixiang XU, Cong HU, Wenzhao YU, Guoquan YAO. Variable depth control of buoyancy regulated UUV with input constraints[J]. Systems Engineering and Electronics, 2022, 44(11): 3496-3504.

Figures/Tables 8

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Variable depth control of buoyancy regulated UUV with input constraints

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