Application of PSO-BP Network Algorithm in AUV Depth Control

Abstract:

In order to improve the depth performance of AUV in parking, a PSO-BP algorithm for the depth control is presented. The algorithm can use the standard particle swarm (PSO) as BP neural network learning method, and which can be evolved in the AUV depth adaptive control. The adaptive controller has adopted the double neural network unit. One of controllers is made use the input terminal to output control quantity on the basis of current displacement and vertical acceleration of the AUV. The other can be recognized on-line by the AUV model identifier. The numerical simulations are given to verify the AUV depth adaptive control by the controller. The results show that the proposed algorithm can significantly improve the AUV depth control performance. The convergence speed of AUV depth control is 4.5 times than the PID algorithm, so the efficiency of the AUV depth is vastly perfected.

• Periodical: Applied Mechanics and Materials (Volumes 321-324)
• Pages: 2025-2031
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.321-324.2025
• Online since: June 2013
• Authors: Qing Yu Hu*, Jun Zhou, Zhi Zha
• Keywords: AUV, BP Network, Depth Control, PSO-BP Algorithm

References

[1] X,X,GUO,G. LI, W.J. YAN: PID Controller Based On GA For AUV Depth Control.J.  Journal of Changchun University of Science and Technology(Natural Science Edition), 2010,33(3):37-39. (In Chinese)

[2] T.T.CHENG, J. LUO,Z.J. TANG,etc. :Dynamic Terminal Sliding Mode Control Method on the Depth Control of AUV.J. Mechanical Engineer, 2010,(9):6-8. (In Chinese)

[3] H.S.XIONG, X.Q. BIAN,X.C. SHI : .Simulation of Robust H∞ Controller for AUV Depth Control.J. Computer Simulation, 2007,24(3):156-159. (In Chinese)

[4] K.M. Hornik, M.Stinchcombe, H.White: Multilayer Feedforward Networks Are Universal Approximators.J. Neural Networks,1989,2(2):359-366.

DOI: 10.1016/0893-6080(89)90020-8

[5] G.C. Chen, J.S.Yu: Particle Swarm Optimization Neural Network and Its Application in Soft-Sensing Modeling[C],ICNC 2005,LNCS 3611/2005:610-617

DOI: 10.1007/11539117_86

[6] J.Kennedy, R.Eberhart: Particle Swarm Optimization[A]，Proc, IEEE International Conference on Neural Networks[C], Piscataway NJ:IEEE Service Center, 1995,1942-1948.

[7] S.A.LIU,Q.Y.HU: Application of PSO-BP network algorithm in optimization of automotive suspension.J. Journal of Jilin University(Engineering and Technology Edition), 2009,39(03):60-65(In Chinese)

[8] X.S. Jiang X.S. Feng D.T. Wang:Unmanned Underwater Vehicles[M]. Liaoning Science and Technology Press, 2000：292—392．(In Chinese)