Diving Control of Autonomous Underwater Vehicle Based on AdaptiveBackstepping Method

doi:10.3969/j.issn.1000-565X.2013.01.003

Journal of South China University of Technology (Natural Science Edition) ›› 2013, Vol. 41 ›› Issue (1): 15-20.doi: 10.3969/j.issn.1000-565X.2013.01.003

• Electronics, Communication & Automation Technology • Previous Articles Next Articles

Diving Control of Autonomous Underwater Vehicle Based on AdaptiveBackstepping Method

Jia He-ming¹ Song Wen-long¹ Chen Zi-yin²

1. College of Electromechanical Engineering, Northeast Forestry University, Harbin 150040, Heilongjiang, China;2. College of Automation, Harbin Engineering University, Harbin 150001, Heilongjiang, China

Received:2012-01-11 Revised:2012-04-29 Online:2013-01-25 Published:2012-12-03
Contact: 宋文龙(1973-),男,博士,教授,主要从事林业智能控制与检测技术研究. E-mail:wlsong139@126.com
About author:贾鹤鸣(1983-),男,博士,副教授,主要从事非线性控制理论及应用研究.E-mail:jiaheminglucky99@126.com
Supported by:
东北林业大学中央高校基本科研业务费专项资金资助项目(DL13BB14);教育部“新世纪优秀人才支持计划冶项目(NCET-10-0279);国家自然科学基金资助项目(30972424)

Abstract

Abstract:

In order to implement precise diving control of the autonomous underwater vehicle (AUV), according tothe kinematic and nonlinear dynamic model of AUV, an adaptive iterative backstepping method based on neuralnetwork is proposed, and a kinematic and dynamic controller is designed. In the investigation, considering theexistence of attack angle and the uncertainties of hydrodynamic damping parameters of the nonlinear model of AUV,a neural network-based controller is designed to on-line estimate the nonlinear hydrodynamic damping terms existingin the pitch motion together with external ocean current disturbances. Then, the adaptive law of the network weightsis presented based on the Lyapunov stability theory to guarantee the uniform ultimate bounding of all signals in theclosed-loop system. Finally, two groups of simulation experiments are carried out to compare the system response ofthe designed controller at a certain control gain and the diving control performance in the presence of disturbances.The results show that the designed controller is of smaller static error and higher tracking precision.

Key words: autonomous underwater vehicle, diving control, backstepping method, neural network, adaptivemethod

Jia He-ming Song Wen-long Chen Zi-yin. Diving Control of Autonomous Underwater Vehicle Based on AdaptiveBackstepping Method[J]. Journal of South China University of Technology (Natural Science Edition), 2013, 41(1): 15-20.

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Diving Control of Autonomous Underwater Vehicle Based on AdaptiveBackstepping Method

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