Autonomous underwater vehicle depth control based on an improved active disturbance rejection controller

• Published in: International journal of advanced robotic systems Vol. 16; no. 6
• Main Authors: Zhang, Zhengzheng, Liu, Bingyou, Wang, Lichao
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 01.11.2019; Sage Publications Ltd; SAGE Publishing
• Subjects: Active control; Autonomous underwater vehicles; Computer simulation; Control systems; Error feedback; Mathematical models; Nonlinearity; Optimal control; Quality control; Rejection; State observers; Tracking; Variations; Vehicles; improved nonlinear state error feedback; autonomous underwater vehicle; Improved active disturbance rejection control; improved extended state observer; depth control
• ISSN: 1729-8806; 1729-8814
• DOI: 10.1177/1729881419891536

Large fluctuation, large overshoot, and uncertain external disturbance that occur when an autonomous underwater vehicle is in deep motion are difficult to address using the traditional control method. An optimal control strategy based on an improved active disturbance rejection control technology is proposed to enhance the trajectory tracking accuracy of autonomous underwater vehicles in actual bathymetric operations and resist external and internal disturbances. First, the depth motion and mathematical models of an autonomous underwater vehicle and propeller are established, respectively. Second, the control rate of the extended state observer and the nonlinear error feedback of the traditional active disturbance rejection control are improved by using a new nonlinear function. The nonlinearity, model uncertainty, and external disturbance of the autonomous underwater vehicle depth control system are extended to a new state, which is realized by an improved extended state observer. Third, the improved nonlinear state error feedback is used to suppress residual errors and provide high-quality control for the system. Simulation and experimental results show that under the same parameters, the traditional active disturbance rejection control has a small overshoot, fast tracking ability, and strong anti-interference ability. The optimized active disturbance rejection control and traditional active disturbance rejection control are applied to the deep-variation motion of autonomous underwater vehicles. Results show that the proposed optimal control strategy is not only simple and feasible but also demonstrates good control performance.