Adaptive dynamic surface control for cooperative path following of underactuated marine surface vehicles via fast learning

Abstract

This study presents a solution to the problem of cooperative path following of multiple underactuated marine surface vehicles subject to dynamical uncertainties and ocean disturbances. The dedicated control designs are categorised into two envelopes. One is to steer individual underactuated marine surface vehicle to track a given spatial path; and the other is to synchronise the along-path speeds and path variables under the constraints of an underlying communication network in order to hold a desired formation pattern. Within these two formulations, a robust adaptive path-following controller is first designed for individual vehicle based on neural networks and a dynamic surface control (DSC) technique. Then, the along-path speeds and path variables are synchronised to each vehicle owing to the proposed decentralised synchronisation control law building on graph theory and Lyapunov theory. The key features of the developed controllers are that, first, the DSC technique simplifies the controller design by introducing first-order filters and avoids the calculation of derivatives of virtual control signals. Second, the developed controllers with filtering adaptive laws allow for fast learning without generating high-frequency oscillations in control signals. Rigorous theoretical analysis demonstrates that all signals in the closed-loop system are uniformly ultimately bounded. Simulation results are provided to show the efficacy of the proposed method.

Cooperative Path Tracking for Swarm of MASSs Based on Consensus Theory

“…Since the Fossen research group first began to study it [5], the path tracking problem of MASS swarm systems has been continuously advanced and developed. Aiming at the path tracking problem of MASS model parameter uncertainty and marine environment disturbance, Wang Hao et al [6,7] proposed a robust adaptive cooperative path tracking algorithm based on a neural network and dynamic surface control technology. Through neural network learning, a high frequency oscillation in the control signal is avoided and a good control effect is obtained.…”

Event‐triggered‐based finite‐time cooperative path following control for underactuated multiple marine surface vehicles

“…The coordinated formation control has been widely used in rescue operation, autonomous exploration and maritime patrol [1,2]. Generally, the coordinated control problem is divided into cooperative path following (CPF) [3], cooperative target tracking [4], and cooperative trajectory tracking [5]. The CPF is to designed cooperative control laws so that MSVS can track predefined parametric paths at a certain velocity.…”

Distributed predictive control of interconnected systems based on disturbance observation

“…Large-scale interconnected systems, such as transportation systems, energy systems, power systems, sewage treatment plants, hydraulic systems [1][2][3][4][5], are widespread in our lives. In general, large-scale systems can be divided into several subsystems according to their locations, functions and characteristics.…”