AUV Vertical Plane Control Based on Improved PID Neural Network Algorithm

doi:10.16182/j.issn1004731x.joss.17-9168

Abstract

Abstract: An improved PID neural network controller is designed for the movement control of a small low-speed autonomous underwater vehicle (AUV) in vertical plane, and the global control of the depth and pitch angle of the underwater vehicle in vertical plane is obtained. The AUV simulation control system is built by using REMUS underwater vehicle model in Simulink. The simulation results show that the improved control method with better dynamic performance has solved the original excessive saturation issue, and can adapt to different learning rates and network initial weight,and is of certain reference value to the practical application of the underwater vehicle.

Key words: low-speed underwater vehicle, improved PID neural network, nonlinear system, multivariable global control, simulink simulation

CLC Number:

TP273.2

Huang Runan, Ding Ning. AUV Vertical Plane Control Based on Improved PID Neural Network Algorithm[J]. Journal of System Simulation, 2020, 32(2): 229-235.

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