Advanced Autonomous Underwater Vehicles Attitude Control with L 1 Backstepping Adaptive Control Strategy

Abstract

This paper presents a novel attitude control design, which combines scriptL1 adaptive control and backstepping control together, for Autonomous Underwater Vehicles (AUVs) in a highly dynamic and uncertain environment. The Euler angle representation is adopted in this paper to represent the attitude propagation. Kinematics and dynamics of the attitude are in the strict feedback form, which leads the backstepping control strategy serving as the baseline controller. Moreover, by bringing fast and robust adaptation into the backstepping control architecture, our controller is capable of dealing with time-varying uncertainties from modeling and external disturbances in dynamics. This attitude controller is proposed for coupled pitch-yaw channels. For inevitable roll excursions, a Lyapunov function-based optimum linearization method is presented to analyze the stability of the roll angle in the operation region. Theoretical analysis and simulation results are given to demonstrate the feasibility of the developed control strategy.

Design and Verification of Deep Submergence Rescue Vehicle Motion Control System

“…The other solution adopts load regulation, including the longitudinal transfer of ballast water, ballast iron or ballast lead. This is energy-saving and can meet the requirement of accuracy at the same time [ 63 , 64 , 65 , 66 , 67 ].…”

Reconfiguration Control Design of UAV against Actuator Faults Based on Control Allocation Method

“…But when the faults occur in the aircraft surface because of actuators, the detection and isolation method based on model cannot work, and it must be reconstructed through the control compensation of other surfaces to achieve fault tolerance. At present, many scholars have proposed adaptive control algorithms to solve various adaptive control problems in the case of surface failure, so as to achieve flight control, but the real-time performance of these algorithms is generally doubted, and a large number of algorithms need accurate mathematical models [12][13][14][15].…”

“…(1) Different from the adaptive control method, as referred to References [12][13][14][15], based on the optimal control law and the fault diagnosis result, control allocation methods carry out the mode switch. It does not need to carry out complex online calculation through the optimization algorithm, so it will not affect the real-time performance…”