Disturbance Observer-Based Anti-Windup Control for Path-Following of Underactuated AUVs via Singular Perturbations: Theory and Experiment

This paper contributes to an anti-windup control scheme for path-following of underactuated autonomous underwater vehicles (AUVs) subject to constrained inputs. First, a disturbance observer is employed to estimate the model uncertainties and external disturbances on the nominal vehicle model, which are referred to as mismatched lumped disturbances. On the basis of that, a three-time scale singular perturbation control law is proposed, taking advantage of the time scale separation caused by the different rates of various variables. Furthermore, a novel disturbance observer-based anti-windup modification is developed to handle possible input saturation. And stability for the singularly perturbed system subject to actuator saturation is also established, using a method called “manifold reconfiguration” in a geometric view. This results in a relatively simple constrained controller and reduces implementation complexity. Finally, simulation and experimental results are presented to substantiate the effectiveness of the proposed method for path-following of underactuated AUVs exposed to unknown disturbances and input constraints.

I. Introduction

Autonomous underwater vehicles (AUVs) play an important role in marine activities as they provide a safe, efficient, and economical alternative that does not put human lives at risk. The motion control scenarios for AUVs mainly include path-following [1], [2], [3], [4], [5], [6], [7], [8], trajectory tracking [9], [10], and formation tracking [11], [12]. In particular, the issue of path-following is relevant to various applications, such as oceanographic survey, target carpet searching, pipeline inspection, and more. As a result, it has garnered significant interest. During the past few years, numerous path-following controllers have been developed for underactuated AUVs with different focuses. In [1], a variational principle of analytical mechanics and Lagrange multiplier was employed to derive a path-following controller for AUVs. In [2], the neurodynamic optimization technique was used to solve the path-following control problem subject to velocity and input constraints. In [3], a model-free robust fuzzy adaptive control scheme was proposed for bottom following of a flight-style AUV with input constraints. In [4], an output-feedback controller was developed for path-following of underactuated AUVs using an extended state observer (ESO) and projection neural networks. In [5], a framework for multi-objective model predictive control (MOMPC) was developed for path-following of AUVs. In [6], the disturbance observer (DO) and linear parameter varying (LPV) technique were introduced to enhance the robust 3D path-following control of underactuated AUVs with multiple uncertainties. In [7], a deep deterministic policy gradient algorithm was proposed for path-following of AUVs, utilizing optimized sample pools and an average motion critic network. In [8], a heuristic fuzzy control scheme was developed for path-following of underactuated AUVs subject to model uncertainties and external disturbances. They have offered new tools and promising solutions for dealing with path-following control of AUVs. However, they usually yield relatively complicated controllers that may be impractical in real-world applications. From a practical perspective, an easy-to-implement nonlinear path-following control law is of great importance.