Spatial Path-Following Control of Underactuated AUV With Multiple Uncertainties and Input Saturation

Abstract

This paper studies the problem of spatial path-following control of underactuated autonomous underwater vehicles (AUVs) with multiple uncertainties and input saturation taken into account. Initially, the reduced-order extended state observes (ESOs) are introduced to estimate and compensate all lumped uncertainties due to the model parameters perturbations, unmodeled dynamics, environmental disturbances, and nonlinear hydrodynamic damping terms. Furthermore, the spatial path-following control strategy is established by combining with backstepping, integral sliding mode control, and estimator to cope with the position, attitude, and linear velocity tracking of the AUV. Specifically, the dynamic surface control (DSC) technique is utilized to achieve satisfactory differential performance and avoid the ''explosion of complexity.'' Additionally, the auxiliary dynamic compensator is presented to analyze the effect of input saturation, and the states of the auxiliary design system are used to develop the controller. It is easily proved that the proposed control scheme can guarantee that all signals of the closed-loop system are globally stable through the Lyapunov theorem, with the tracking errors converging to an arbitrarily small neighborhood of zero. Finally, the numerical simulation results are carried out to illustrate the effectiveness of the proposed controller.INDEX TERMS AUV, path-following, multiple uncertainties, input saturation, time-varying sideslip angle.

Robust Path-Following Control of Underactuated AUVs with Multiple Uncertainties in the Vertical Plane

“…(2) To eliminate the effect of input saturation and handle the "explosion of complexity" associated with a traditional backstepping method, an NTD is utilized to track the virtual control signal and its derivative. Compared with the traditional dynamic surface control method presented in [18,38], the NTD is a time-optimal solution that provides the fastest tracking of the input signal [29]. (3) Based on the constructed reduced-order ESOs and NTD, an augmented back-stepping controller is constructed to enhance the robustness against the external environment disturbances, the perturbations in the internal model parameters, and other unmodeled dynamics.…”

Adaptive neural network-based path tracking control for autonomous combine harvester with input saturation

“…Input saturation is another issue attentioned. The existing control methods mainly restrict the control input during the output process, but do not consider in the design process, which may cause the round-trip operation of the actuator (Hu et al , 2019; Guo et al , 2019). Thus, to improve the path tracking accuracy and environmental adaptability, an adaptive neural network-based path tracking controller with input saturation is designed for the autonomous combine harvester.…”

Event-Based Path-Planning and Path-Following in Unknown Environments for Underactuated Autonomous Underwater Vehicles

“…Once a path is generated, one needs to make the AUV follow the path accurately, when considiering its dynamic model, control constraints, and kinematics. A wide diversity of methods have been developed in order to solve the path-following problem, among which are backstepping method [22][23][24], observer-based method [25], nonlinear PID control [26], adaptive control [27], model predictive control [21,28], sliding mode control [5,29], and fuzzy control [30]. In the context of the simultaneous solution of path-planning and path-following problems, we note the studies presented in [5,20,21,31].…”