DO-LPV-based robust 3D path following control of underactuated autonomous underwater vehicle with multiple uncertainties. (June 2020)

• Record Type: Journal Article
• Authors: Zhang, Yuwei; Wang, Xingjian; Wang, Shaoping; Miao, Jianming
• Is Part Of: ISA transactions. Volume 101(2020)
• Page Start: 189
• Page End: 203
• Publication Date: 2020-06
• Subjects: Autonomous underwater vehicle -- Path following -- Multiple uncertainties -- Disturbance observer -- Linear parameter varying control; Engineering instruments -- Periodicals; Engineering instruments; Periodicals; Electronic journals; 629.805
• DOI: 10.1016/j.isatra.2020.01.017
• Languages: English
• ISSNs: 0019-0578

Abstract

Abstract: This study investigates a path following problem of underactuated autonomous underwater vehicle under multiple uncertainties in three-dimensional space. The uncertainties are partly induced by hydrodynamic coefficient uncertainty, ocean currents and unmodeled hydrodynamics, namely dynamic uncertainties. In addition, velocities are assumed to be measured with bounded noise, which is called velocity measurement uncertainties. To address this issue, a compound robust path following control strategy is developed. At the kinematic level, an improved kinematic controller is developed by utilizing disturbance observer to recover the unknown time-varying attack and side-slip angular velocity. At the dynamic level, a novel dynamic tracking model is firstly established via linear parameter varying (LPV) technique, by which multiple uncertainties are expressed in a comprehensive way. Subsequently, a robust LPV controller is employed to track desired velocities generated by kinematic controller, which has less dependence on accurate model and exact velocity measurement. Finally, rigorous stability analysis proves the uniform and ultimate boundedness of path following errors. The comparative numerical results also substantiate the efficacy and superiority of designed method. Highlights: A robust path following strategy for underactuated AUV is proposed. The velocity measurement uncertainties are firstly considered. A novel dynamic tracking model is firstly established via LPV technique. The method includes DO-based kinematic controller and LPV-based dynamic controller. Comparative simulation results validate the effectiveness of proposed controller.