Neural network based robust adaptive dynamic surface control for AUVs - Details

author：

Miao, Bao-Bin (Miao, Bao-Bin.) ^[1] | Li, Tie-Shan (Li, Tie-Shan.) ^[2] | Luo, Wei-Lin (Luo, Wei-Lin.) ^[3] (Scholars：罗伟林)

Indexed by：

EI Scopus

Abstract：

A　neural　network　controller　is　presented　for　tracking　control　of　underwater　vehicles　with　uncertainties.　By　employing　the　neural　network　method　to　account　for　system　uncertainties,　the　proposed　scheme　is　developed　by　combining　＇dynamic　surface　control(DSC)＇.　Consequently,　the　problem　of　＇explosion　of　complexity＇　inherent　in　the　conventional　backstepping　method　is　avoided.　Modeling　errors　and　environmental　disturbance　are　considered　in　the　mathematical　model.　A　two-layer　neural　network　is　introduced　to　compensate　the　modeling　errors,　while　the　effect　of　the　environmental　disturbance　is　addressed　by　using　the　property　of　hyperbolic　tangent　function.　Under　the　developed　tracking　control　approach,　semi-global　uniform　boundedness　of　all　closed-loop　signals　are　guaranteed　via　Lyapunov　analysis.　Simulation　studies　are　given　to　illustrate　the　effectiveness　of　the　proposed　tracking　control.　Copyright　©　2013　IFAC.

Keyword：

Adaptive control systems Hyperbolic functions Intelligent control Multilayer neural networks Navigation Network layers

Community：

[ 1 ] [Miao, Bao-Bin]Navigational College, Dalian Maritime University, Dalian 116026, China
[ 2 ] [Li, Tie-Shan]Navigational College, Dalian Maritime University, Dalian 116026, China
[ 3 ] [Luo, Wei-Lin]College of Mechanical Engineering and Automation, Fuzhou University, Fujian 350108, China