A neural network adaptive controller design for free-pitch-angle diving behavior of an autonomous underwater vehicle

2005 ◽  
Vol 52 (2-3) ◽  
pp. 132-147 ◽  
Author(s):  
Ji Hong Li ◽  
Pan Mook Lee
Keyword(s):  
Neural Network ◽  
Pitch Angle ◽  
Autonomous Underwater Vehicle ◽  
Controller Design ◽  
Adaptive Controller ◽  
Underwater Vehicle ◽  
Diving Behavior

scholarly journals Underwater terrain-aided navigation method based on improved Gaussian sum particle filtering

2019 ◽  
Vol 16 (1) ◽  
pp. 172988141882157
Author(s):  
Pengyun Chen ◽  
Jianlong Chang ◽  
Yujie Han ◽  
Meini Yuan
Keyword(s):  
Neural Network ◽  
Radial Basis Function ◽  
Particle Filter ◽  
Basis Function ◽  
Particle Filtering ◽  
Autonomous Underwater Vehicle ◽  
Underwater Vehicle ◽  
Gaussian Sum ◽  
Matching Performance ◽  
Navigation Method

To solve the nonlinear Bayesian estimation problem in underwater terrain-aided navigation, a terrain-aided navigation method based on improved Gaussian sum particle filter is proposed. This method approximates the Bayesian function using multiple Gaussian components, and the components can be obtained by radial basis function neural network. This method has no resampling process, the particle depletion of particle filtering is eliminated in principle. The simulation shows that the proposed method has good matching performance, which is suitable for autonomous underwater vehicle navigation.

scholarly journals Analysis of Parameter Sensitivity Using Robust Design Techniques for a Flatfish Type Autonomous Underwater Vehicle

2009 ◽  
Vol 2009 ◽  
pp. 1-10 ◽  
Author(s):  
M. Santhakumar ◽  
T. Asokan ◽  
T. R. Sreeram
Keyword(s):  
Robust Design ◽  
Pitch Angle ◽  
High Performance ◽  
Autonomous Underwater Vehicle ◽  
Controller Design ◽  
Autonomous Underwater Vehicles ◽  
Angle Variation ◽  
Hydrodynamic Parameters ◽  
And Control ◽  
Design Techniques

Hydrodynamic parameters play a major role in the dynamics and control of Autonomous Underwater Vehicles (AUVs). The performance of an AUV is dependent on the parameter variations and a proper understanding of these parametric influences is essential for the design, modeling, and control of high-performance AUVs. In this paper, the sensitivity of hydrodynamic parameters on the control of a flatfish type AUV is analyzed using robust design techniques such as Taguchi's design method and statistical analysis tools such as Pareto-ANOVA. Since the pitch angle of an AUV is one of the crucial variables in the control applications, the sensitivity analysis of pitch angle variation is studied here. Eight prominent hydrodynamic coefficients are considered in the analysis. The results show that there are two critical hydrodynamic parameters, that is, hydrodynamic force and hydrodynamic pitching moment in the heave direction that influence the performance of a flatfish type AUV. A near-optimal combination of the parameters was identified and the simulation results have shown the effectiveness of the method in reducing the pitch error. These findings are significant for the design modifications as well as controller design of AUVs.

Mu-Synthesis Depth Controller Design for a Small Autonomous Underwater Vehicle

2012 ◽  
Vol 15 (1) ◽  
pp. 202-209 ◽  
Author(s):  
Mai Ba Loc ◽  
Hyeung-Sik Choi ◽  
Sam-Sang You ◽  
Joonyoung Kim ◽  
Yun-Hae Kim
Keyword(s):  
Autonomous Underwater Vehicle ◽  
Controller Design ◽  
Underwater Vehicle ◽  
Mu Synthesis
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