Adaptive Sliding Mode Control for Depth Trajectory Tracking of Remotely Operated Vehicle with Thruster Nonlinearity. (28th July 2016)

• Record Type: Journal Article
• Authors: Chu, Zhenzhong; Zhu, Daqi; Yang, Simon X.; Jan, Gene Eu
• Is Part Of: Journal of navigation. Volume 70:Number 1(2017)
• Page Start: 149
• Page End: 164
• Publication Date: 2016-07-28
• Subjects: Remotely operated vehicle, -- Trajectory tracking, -- Adaptive control, -- Sliding mode control, -- Thruster nonlinearity; Navigation -- Periodicals; 623.8905
• DOI: 10.1017/S0373463316000448
• Languages: English
• ISSNs: 0373-4633

Abstract

Abstract : This paper focuses on depth trajectory tracking control for a Remotely Operated Vehicle (ROV) with dead-zone nonlinearity and saturation nonlinearity of thruster; an adaptive sliding mode control method based on neural network is proposed. Through the analysis of dead-zone nonlinearity and saturation nonlinearity of thruster, the depth trajectory tracking control system model of a ROV which uses thruster control signals as system input has been established. According to the principle of sliding mode control, an adaptive sliding mode depth trajectory tracking controller is built by using three-layer feed-forward neural network for online identification of unknown items. The selection method and update laws of the control parameters are also given. The uniform ultimate boundedness of trajectory tracking error is analysed by Lyapunov theorem. Finally, the effectiveness of the proposed method is illustrated by simulations.