Robust Adaptive Control for Nonlinear Path Tracking of Unmanned Surface Vehicles

doi:10.3969/j.issn.1000-1093.2019.12.017

Abstract

Abstract: A robust adaptive control approach based on cubic Hermite spline interpolation (CHSI) and neural network is proposed for the path tracking of underactuated unmanned surface vehicles (USVs). A smooth nonlinear desired path is obtained by using CHSI method to fit the way-point, which solves the problem of swing and twist of USV caused by traditional linear path. Based on the Serret-Frenet frame, an adaptive line-of-sight (ALOS) guidance law is setablished to improve the rate of convergence and reduce the oscillation. Considering the influence of model uncertainties of USV and environmental distur- bance, a concise robust adaptive neural network controller was developed. The proposed control strategy can effectively improve the accuracy and quality of path tracking control, and has the advantages of less learning parameters and computing load. The convergence of the system is proven through stability analysis, and the effectiveness of the proposed control scheme is verified by using the simulation examples. Key

Key words: unmannedsurfacevehicle, pathtracking, adaptivecontrol, nonlinearsystem, neuralnetwork

CLC Number:

LUO Fuyu, ZENG Jiangfeng, AI Ning. Robust Adaptive Control for Nonlinear Path Tracking of Unmanned Surface Vehicles[J]. Acta Armamentarii, 2019, 40(12): 2519-2528.

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第40卷
第12期2019 年12月兵工学报ACTA
ARMAMENTARIIVol.40No.12Dec.2019

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