  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.
