ADP based trajectory-tracking control via backstepping method for underactuated AUV with unknown dynamics

This paper investigates trajectory-tacking control problem for underactuated autonomous underwater vehicles (AUV) with unknown dynamics. Different from existing adaptive dynamic programming (ADP) schemes, our proposed control scheme can achieve high-level system stability and tracking control accuracy. Firstly, the backstepping approach is introduced into the kinematic model of underactuated AUV and produces a virtual velocity control which is taken as the desired velocity input of the dynamic model of underactuated AUV. Secondly, the error tracking system is constructed according to the dynamic model of underactuated AUV. Thirdly, the critic neural network and the action neural network are employed to transform the trajectory-tracking control problem into optimal control problem based on policy iteration algorithm. At last simulation results are given to verify the effectiveness of the control scheme proposed in this paper.

ADP Based Fault-Tolerant Tracking Control for Underactuated AUV with Actuators Faults via Neural Network Observer

In this work, the fault-tolerant tacking control issue of underactuated autonomous underwater vehicle (AUV) with actuators faults is investigated. Firstly, an output-feedback error tacking system is constructed based on the theoretical model of underactuated AUV with actuators faults. Then, an adaptive dynamic programming (ADP) based fault-tolerant control controller is developed. In our proposed control scheme, a neural-network observer is designed to approximate the system states with actuators faults. A novel ADP scheme is constructed with critic neural network and action neural network in order to reduce the jitter in the control input and improve the tracking accuracy. Based on Lyapunov approach, the stability of the error tracking system is guaranteed by the proposed controller. At last, the simulation results show that the underactuated AUV achieves better tracking performance.

The path-following control of the underactuated AUV with input saturation and multiple disturbances

Autonomous underwater vehicle (AUV) in marine resource surveys plays an important role. This paper proposes a new path-following control frame for the underactuated AUV with input saturation and multiple disturbances. The disturbances include external disturbances, model parameter uncertainties, unmodeled dynamics and other random disturbances. Compared to most of previously published literatures, which treat disturbances as lumped disturbances, a composite hierarchical anti-disturbance control (CHADC) strategy is adopted to achieve higher precision path following. A disturbance observer (DOB) is constructed to estimate and eliminate the disturbances with partial known information, while the H ∞ theory is used to optimize the path-following controller to attenuate the other disturbances satisfying the L 2-norm bound condition and improve the robustness of system. Besides, Lyapunov direct method and back-stepping method are used to design the path-following controller, where the input saturation is considered, the extended state observer (ESO) is used to estimate the uncertainty of kinematic controller and the nonlinear tracking differentiator (NTD) is used to simplify the controller. Finally, simulations are given to demonstrate the effectiveness of the proposed control law.