Learning from adaptive neural network output feedback control of uncertain ocean surface ship dynamics

DOI10.1002/acs.2366zbMath1331.93109OpenAlexW1641957729MaRDI QIDQ2795799

Liejun Li, Cong Wang, Shi-Lu Dai, Min Wang

Publication date: 22 March 2016

Published in: International Journal of Adaptive Control and Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/acs.2366

zbMATH Keywords

learningoutput feedbackship controluncertain dynamicsadaptive neural network (NN) controlpartial persistent excitation (PE) condition

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Feedback control (93B52) Control/observation systems with incomplete information (93C41) Application models in control theory (93C95) Adaptive control/observation systems (93C40) Control/observation systems governed by ordinary differential equations (93C15)

Related Items (5)

Robust adaptive control of a thruster assisted position mooring system ⋮ Adaptive finite-time sliding mode control design for finite-time fault-tolerant trajectory tracking of marine vehicles with input saturation ⋮ Neural prescribed performance control for uncertain marine surface vessels without accurate initial errors ⋮ Some recent advances in learning and adaptation for uncertain feedback control systems ⋮ Robust adaptive steering control for unmanned surface vehicle with unknown control direction and input saturation

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