Title: Intelligent control algorithm for USV with input saturation based on RBF network compensation

Authors: Renqiang Wang; Keyin Miao; Jianming Sun; Jingdong Li; Dawei Chen

Addresses: Navigation College, Jiangsu Maritime Institute, No. 309, Gezhi Road, Jiangning District, Nanjing, China ' Navigation College, Jiangsu Maritime Institute, No. 309, Gezhi Road, Jiangning District, Nanjing, China ' Navigation College, Jiangsu Maritime Institute, No. 309, Gezhi Road, Jiangning District, Nanjing, China ' Navigation College, Jiangsu Maritime Institute, No. 309, Gezhi Road, Jiangning District, Nanjing, China ' Navigation College, Jiangsu Maritime Institute, No. 309, Gezhi Road, Jiangning District, Nanjing, China

Abstract: A type of intelligent control algorithm of course tracking for USV was proposed on the basis of RBF network approximation and compensation with input saturation. Firstly, sliding surfaces with integrator were designed on the basis of sliding mode control technology. Secondly, radial basis function neural network was applied to approximate compensating the system input saturation. Thirdly, second-order system observer was introduced to overcome the bounded outside interference. Finally, the control algorithm for USV was deduced by backstepping method with Lyapunov theory. Simulation result indicated that the intelligent control algorithm is suitable for USV.

Keywords: USV motion control; intelligent control; RBF neural network; sliding mode control; saturation.

DOI: 10.1504/IJRIS.2019.102562

International Journal of Reasoning-based Intelligent Systems, 2019 Vol.11 No.3, pp.235 - 241

Received: 03 Mar 2018
Accepted: 27 Aug 2018
Published online: 30 Sep 2019 *

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