Depth control of an Autonomous underwater vehicle (AUV) using neural sliding mode controller

Depth control autonomous underwater vehicle due to disturbances, noise and non-linear dynamics is very important and difficult in the field of systems control and for the solving it in methods that are robust to the uncertainty of the system is needed. To deal with such uncertainties and disturbances, sliding mode control has been used. Generally, The main advantage of this method is robust to uncertainties and disturbances, But due to the computational delays and restrictions on operators immediately change is not possible and leads to the phenomenon of chattering in control signal and excitation high-frequency dynamics. In this paper, depth control of an autonomous underwater vehicle is considered. To solve the problem chattering in the system under study, We tried to be used the combination of sliding mode control and artificial neural network. The use of the artificial neural network has led to the estimation of the uncertainties of the system and the chattering domain in the control signal is effectively reduced. Simulation show that the sliding mode method problems in depth control of underwater vehicle using artificial neural network capabilities has been fixed and the system properly controlled.