A Comprehensive Study on Modelling and Control of Autonomous Underwater Vehicle

TL;DR

This work develops a comprehensive 6‑DoF model for an Autonomous Underwater Vehicle (AUV) that incorporates ocean currents, added mass, and hydrodynamic effects, and demonstrates level-flight (trim) analysis to derive robust control strategies. By decomposing the dynamics into vertical (depth–pitch) and horizontal (heading–yaw) subsystems, the study designs and compares linear controllers with nonlinear approaches, including conventional nonlinear control and Sliding Mode Control (SMC), under disturbances such as ocean currents and CG/buoyancy variations. Level-flight results at $U=4$ knots and lawn-mowing maneuvers illustrate performance and robustness trade-offs, with SMC showing enhanced disturbance rejection at the expense of increased complexity and potential chattering. The findings provide a practical framework for robust AUV control in harsh underwater environments and highlight the balance between controller robustness and implementation complexity.

Abstract

Autonomous underwater vehicles (AUV) have become the de facto vehicle for remote operations involving oceanography, inspection, and monitoring tasks. These vehicles operate in different and often challenging environments; hence, the design and development of the AUV involving hydrodynamics and control systems need to be designed in detail. This book chapter presents a study on the modelling and robust control of a research vehicle in the presence of uncertainties. The vehicle's dynamic behaviour is modelled using a 6-degree-of-freedom approach, considering the effect of ocean currents. The level flight requirements for different speeds are derived, and the resulting model is decomposed into horizontal and vertical subsystems for linear analysis. The simulation results presented focus on the efficacy of linear controllers within three key subsystems: depth, yaw, and speed. Moreover, level-flight outcomes are demonstrated for a speed of 4 knots. The nonlinear control strategies employed in this study encompass conventional and sliding-mode control (SMC) methodologies. To ensure accurate tracking performance, the controller design considers the vehicle's dynamics with various uncertainties such as ocean currents, parameter uncertainty, CG (Center of Gravity) deviation and buoyancy variation. Both conventional and nonlinear SMC controllers' outcomes are showcased with a lawn-mowing manoeuvre scenario. A systematic comparison is drawn between the robustness of SMC against disturbances and parameter fluctuations in contrast to conventional controllers. Importantly, these results underscore the trade-off that accompanies SMC's robustness, as it necessitates a higher level of complexity in terms of controller design, intricate implementation intricacies, and the management of chattering phenomena.

Figures (14)

• Figure 1: Body-fixed and Earth-fixed Coordinate Systems
• Figure 3: Schematic of Depth - pitch subsystem with controller
• Figure 4: Depth, pitch and stern angle of depth subsystem
• Figure 5: Schematic of yaw subsystem with controller
• Figure 6: Lateral position, yaw and rudder angle of yaw subsystem