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Robust adaptive regulation of dynamically positioned ships with unknown dynamics and unknown disturbances
Author(s) -
Hu Xin,
Du Jialu,
Krstić Miroslav
Publication year - 2019
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.2972
Subject(s) - control theory (sociology) , backstepping , bounded function , adaptive control , robust control , term (time) , heading (navigation) , computer science , dead zone , artificial neural network , position (finance) , dynamic positioning , control (management) , engineering , control system , mathematics , artificial intelligence , physics , mathematical analysis , oceanography , finance , quantum mechanics , aerospace engineering , geology , marine engineering , electrical engineering , economics
Summary We develop a robust adaptive regulating control law for dynamically positioned ships subject to unknown dynamics and bounded unknown disturbances incorporating the radial basis function (RBF) neural network (NN), the dead zone adaptive technique, and a robust control term into the vectorial backstepping approach. The RBF NNs with the dead zone adaptive laws approximate the ship unknown dynamics. The adaptive law‐based robust control term compensates for unknown disturbances, NN approximation errors, and undesirable errors arising from the design procedures. The developed dynamic positioning (DP) control law regulates the ship position and heading to the desired values with arbitrarily small errors, while guaranteeing the uniform ultimate boundedness of all signals in the DP closed‐loop control system of ships. High‐fidelity simulations on two supply ships and comparisons demonstrate the effectiveness and the superiority of the developed DP control law.