Robust adaptive regulation of dynamically positioned ships with unknown dynamics and unknown disturbances

• Published in: International journal of adaptive control and signal processing Vol. 33; no. 3; pp. 545 - 556
• Main Authors: Hu, Xin, Du, Jialu, Krstić, Miroslav
• Format: Journal Article
• Language: English
• Published: Bognor Regis Wiley Subscription Services, Inc 01.03.2019
• Subjects: Adaptive control; Basis functions; Computer simulation; Control theory; Disturbances; Laws; Neural networks; Radial basis function; robust adaptive control; Robust control; ship dynamic positioning; Ships; Supply ships; unknown dynamics; unknown time‐varying disturbances; vectorial backstepping
• ISSN: 0890-6327; 1099-1115
• DOI: 10.1002/acs.2972

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.