Adaptive Formation Switching Control of Multi-AUVs for Target Tracking with State Estimation

Abstract

This paper aims to study dynamic behavior of multiple autonomous underwater vehicles (AUVs) in formation for target tracking. During the tracking task using a team of AUVs, some of the trackers may suffer a sudden system failure due to the communication or power issues in the complex and harsh underwater environment. Therefore, an adaptive formation switching method based on model predictive control (MPC) strategy is used to motion control of multi-AUVs, when some of the trackers unexpectedly dropped out of the team. The control scheme consists of state estimation module and formation switching control module. Firstly, the states of maneuvering target are estimated using EKF based on constant turn rate and velocity (CRTV) motion model. Secondly, a formation switching control strategy is proposed using the designed parameterized virtual reference points. A nonlinear model predictive controller is proposed to achieve the dynamic formation. Simulation results showed high formation tracking accuracy and feasibility of adaptive formation switching control strategy under the reasonable assumption of underwater communication conditions. Moreover, the proposed control scheme would enable the multi-AUVs to continuously track the moving target by adaptively switching the formation when one of the trackers encounters sudden failure and the number of tracking team members varies.