Sliding mode Control of an Autonomous Underwater vehicle with Parametric uncertainty and Sensors Noises

Sliding mode control, due to its great robustness, is very effective approach for underwater vehicles. Due to complexity of underwater environment and existence of disturbance, robust controllers such as sliding mode control have appropriate results in experimental tests. In this paper, sliding mode control has been used for depth channel and steering channel. It has been used for linear and nonlinear systems with parametric uncertainty and sensor noise. Kalman filter observer has been applied to estimate the values of state variables of the underwater vehicle dynamic system that is excited by stochastic disturbances and stochastic measurement noise. Simulation results show that the proposed method is effective in control of depth and steering of the AUV and show that this method can obtain high precision tracking control performance.