caa a22 4500 606159274 CHVBK 20210128100624.0 cr unu---uuuuu 210128e20151001xx s 000 0 eng 10.1007/s00521-015-1821-3 doi (NATIONALLICENCE)springer-10.1007/s00521-015-1821-3 Path following of underactuated surface vessels with fin roll reduction based on neural network and hierarchical sliding mode technique [Elektronische Daten] [Cheng Liu, Zao-jian Zou, Tie-shan Li] Path following and fin roll reduction of underactuated surface vessels, which have been studied separately, are studied simultaneously in this paper. The surge force, roll moment and yaw moment are perceived as control inputs, while the position, roll angle and yaw angle are to be controlled. Hierarchical sliding mode technique is employed to deal with the underactuation of the system. In order to cope with the uncertainties and nonlinearities, the radial basis function neural network is incorporated with hierarchical sliding mode technique. Stability is proved based on Lyapunov stability theorem. Various simulations under random wave disturbances are conducted to verify the performance of the designed controllers. The Natural Computing Applications Forum, 2015 Underactuated surface vessels nationallicence Hierarchical sliding mode nationallicence Neural network (NN) nationallicence Path following (PF) nationallicence Fin roll reduction (FRR) nationallicence Liu Cheng School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, 200240, Shanghai, China aut Zou Zao-jian School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, 200240, Shanghai, China aut Li Tie-shan Navigation College, Dalian Maritime University, 116026, Dalian, Liaoning, China aut Neural Computing and Applications Springer London 26/7(2015-10-01), 1525-1535 0941-0643 26:7<1525 2015 26 521 https://doi.org/10.1007/s00521-015-1821-3 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00521-015-1821-3 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Liu Cheng School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, 200240, Shanghai, China aut NATIONALLICENCE 700 1- Zou Zao-jian School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, 200240, Shanghai, China aut NATIONALLICENCE 700 1- Li Tie-shan Navigation College, Dalian Maritime University, 116026, Dalian, Liaoning, China aut NATIONALLICENCE 773 0- Neural Computing and Applications Springer London 26/7(2015-10-01), 1525-1535 0941-0643 26:7<1525 2015 26 521