Robust path-following control of the underactuated AUV with multiple uncertainties using combined UDE and UKF

• Published in: Journal of marine science and technology Vol. 28; no. 4; pp. 804 - 818
• Main Authors: Miao, Jianming, Liu, Wenchao, Peng, Chao, Sun, Xingyu
• Format: Journal Article
• Language: English
• Published: Tokyo Springer Japan 01.12.2023; Springer; Springer Nature B.V
• Subjects: Analysis; Automotive Engineering; Autonomous underwater vehicles; Comparative analysis; Components; Disturbances; Ecosystem disturbance; Engineering; Engineering Design; Engineering Fluid Dynamics; Kalman filters; Marine environment; Mechanical Engineering; Noise measurement; Numerical analysis; Offshore Engineering; Original Article; Parameter uncertainty; Remote submersibles; Robust control; Simulation methods; Uncertainty; Underwater vehicles; Uncertainty and disturbance estimator (UDE); Autonomous underwater vehicle (AUV); Unscented Kalman filter (UKF)
• ISSN: 0948-4280; 1437-8213
• DOI: 10.1007/s00773-023-00958-1

In the complex ocean environment, the autonomous underwater vehicle (AUV) is subject to the multiple uncertainties including deterministic uncertainties and stochastic uncertainties, which greatly degrade the control performance. To solve this problem, a novel robust control strategy using combined uncertainty and disturbance estimator (UDE) and unscented Kalman filter (UKF) is proposed for the path-following control (PFC) of the underactuated AUV under multiple uncertainties in this paper. First, the UDE technique is adopted to handle the deterministic uncertainties, including deterministic components of environmental disturbances, parameter uncertainties, and unmodeled dynamics, etc. Second, the uncertainty of unactuated lateral channel, which cannot be dealt with by the UDE, is treated as an unknown parameter. Also, to tackle the stochastic uncertainties, which is often ignored in previous studies, including stochastic components of environmental disturbances, measurement noise, and the estimation errors of UDE which are treated as the process noise, the augmented UKF technique is adopted to jointly estimate the system states and the lateral channel unknown parameter. Finally, extensive numerical simulations and comparative analyses are presented to verify the efficiency and robustness of the proposed control strategy.