Depth Control of Autonomous Underwater Vehicle Using Discrete Time Sliding Mode Controller

Depth control of remotely operated underwater vehicles using an adaptive fuzzy sliding mode controller

Sliding mode control, due to its robustness against modelling imprecisions and external disturbances, has been successfully employed to the dynamic positioning of remotely operated underwater vehicles. In order to improve the performance of the complete system, the discontinuity in the control law must be smoothed out to avoid the undesirable chattering effects. The adoption of a properly desig...

Adaptive fuzzy sliding mode controller for the snorkel underwater vehicle

This paper describes a control system for the kinematic variables of an underwater vehicle. Control of underwater vehicles is not simple, mainlys due to the nonlinear, coupled and unknown character of system equations and dynamics. The proposed methodology makes use of a pioneering algorithm implemented for the first time in an underwater vehicle, and it is based on the fusion of a sliding mode...

OPTIMIZED FUZZY CONTROL DESIGN OF AN AUTONOMOUS UNDERWATER VEHICLE

In this study, the roll, yaw and depth fuzzy control of an Au- tonomous Underwater Vehicle (AUV) are addressed. Yaw and roll angles are regulated only using their errors and rates, but due to the complexity of depth dynamic channel, additional pitch rate quantity is used to improve the depth loop performance. The discussed AUV has four aps at the rear of the vehicle as actuators. Two rule bases...

Discrete-time sliding mode control for MR vehicle suspension system

Design of an adaptive nonlinear controller for depth control of an autonomous underwater vehicle

This paper presents an adaptive nonlinear controller for diving control of an autonomous underwater vehicle (AUV). So far, diving dynamics of an AUV has often been derived under various assumptions on the motion of the vehicle. Typically, the pitch angle of AUV has been assumed to be small in the diving plane. However, these kinds of assumptions may induce large modeling errors and further may ...