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Adaptive Backstepping Sliding Mode Tracking Control For Autonomous Underwater Vehicles With Input Quantization

Shun An, Longjin Wang, Yan He, Jianping Yuan

2022Advanced Theory and Simulations28 citationsDOI

Abstract

Abstract This paper proposes an adaptive backstepping sliding mode control (ABSMC) scheme for autonomous underwater vehicles (AUVs) subject to the dynamic uncertainty, external disturbance and quantization error. The control input signals including control forces and moment are quantized by a hybrid quantizer which is the combinination of a logarithmic quantizer and a uniform quantizer. The kinematic controller is designed by the backstepping control technique and the dynamic controller is developed using the sliding mode control method. In order to further improve the robustness of the closed‐loop system, an adaptive law is employed to estimate the upper bound of the total uncertainties in real time. The stability of the closed‐loop system is proved based on the Lyapunov theory and indicates that the proposed control method can force the AUV to track the desired trajectory. Simulation results demonstrate the effectiveness of the proposed control strategy.

Topics & Concepts

BacksteppingControl theory (sociology)Sliding mode controlRobustness (evolution)Computer scienceLyapunov stabilityQuantization (signal processing)KinematicsLyapunov functionAdaptive controlController (irrigation)Control engineeringEngineeringNonlinear systemControl (management)Artificial intelligenceAlgorithmPhysicsChemistryBiologyAgronomyQuantum mechanicsClassical mechanicsBiochemistryGeneAdaptive Control of Nonlinear SystemsUnderwater Vehicles and Communication SystemsStability and Control of Uncertain Systems
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