Trajectory Tracking Control for Underactuated Autonomous Underwater Vehicles Using Dual Close-Loop TMPC

This paper addresses the three-dimensional (3-D) trajectory tracking of underactuated autonomous underwater vehicles (AUVs) in intricate ocean environments. A dual closed-loop tube-based model predictive control (TMPC) scheme is presented to improve trajectory tracking performance and system robustness by online optimization and state feedback, wihch considers the model uncertainties and external disturbances. There are two components to the outer-loop control law: an online control law, which is the optimal solution obtained by solving a Finite-Horizon Optimal Control Problem (FHOCP), and an offline state feedback law that guarantees the actual trajectory is in the bounded tube centered along the nominal trajectory. The inner-loop velocity controller generates feasible control inputs for the closed-loop tracking control. The controller takes the input and state constraints into account. Furthermore, the stability analysis based on the input-to-state stable (ISS) method proves that the closed-loop control system is stable. Finally, the tracking effectiveness and feasibility of the proposed controller with external disturbances have been confirmed by simulation results.

1 Introduction

To satisfy the demands of environmental safety and ma-rine exploration, AUV research has become more and more popular due to high mobility and advanced intelligence^[2]. In the past decades, AUVs have played a significant role in applications such as natural pipeline leakage prevention, sub-sea deployment of cables and pipelines, accident site search and rescue, and site exploration^[12]. AUVs have significantly reduced human risks and improved the ability to explore undiscovered oceans^[3]. The 3-D trajectory tracking control of AUVs is facing challenges due to complex underwater environments, underactuativity, system constraints, and high cross-coupling^[9].