Three-dimensional optimal trajectory tracking control of underactuated AUVs with uncertain dynamics and input saturation

In practice, the energy consumption of underactuated autonomous underwater vehicles (AUVs) is an essential factor to consider. Also, uncertain dynamics, actuator saturation, and unknown environmental disturbances affect control performance. To this end, a three-dimensional optimal trajectory tracking control scheme for underactuated AUVs with environmental disturbances, uncertain dynamics, and input saturation is proposed. First, a continuous differentiable asymmetric saturation model is designed to handle input saturation. Then, the underactuated problem is solved by redefining system outputs. An adaptive neural network observer is developed to estimate disturbances and uncertain dynamic parts. Next, an adaptive backstepping controller is developed via adaptive control and backstepping techniques to obtain a new affine nonlinear system while reducing the effects of input saturation and estimation errors. An optimal controller that can optimize energy consumption and tracking errors is designed via adaptive dynamic programming. Finally, actual control inputs are obtained by combining observer estimates, adaptive backstepping control inputs, approximate optimal control inputs, and the saturation model. Theoretical analysis shows that all signals of the AUV control system are uniformly ultimately bounded, and tracking errors can converge to an arbitrarily small compact set of the origin. Simulation results prove the effectiveness and superiority of the proposed scheme.