Fuzzy neural network-based robust adaptive control for dynamic positioning of underwater vehicles with input dead-zone

DOI10.3233/IFS-151961zbMath1361.93046MaRDI QIDQ2987820

Chengcheng Pang, Jingjing Xue, Guoqing Xia

Publication date: 18 May 2017

Published in: Journal of Intelligent & Fuzzy Systems (Search for Journal in Brave)

zbMATH Keywords

dead-zoneunderwater vehicledynamic recurrent fuzzy neural networkdynamic positioningfuzzy compensator

Mathematics Subject Classification ID

Sensitivity (robustness) (93B35) Fuzzy control/observation systems (93C42) Application models in control theory (93C95) Adaptive control/observation systems (93C40)

Related Items (4)

Constrained control for a class of vessel operations: positioning under environmental and shielding effects ⋮ A nonlinear robust controller design for ship dynamic positioning based on \(L_2\)-gain disturbance rejection ⋮ Uncertainty observation-based adaptive succinct fuzzy-neuro dynamic surface control for trajectory tracking of fully actuated underwater vehicle system with input saturation ⋮ Adaptive sliding mode fixed-time tracking control based on fixed-time sliding mode disturbance observer with Dead-zone input

Cites Work

• Single input fuzzy logic controller for unmanned underwater vehicle
• Adaptive dynamic surface control of nonlinear systems with unknown dead zone in pure feedback form
• Deadzone compensation in motion control systems using neural networks
• A novel error observer-based adaptive output feedback approach for control of uncertain systems

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