Leader-Following Entrapping Control of AUVs Using Bearing Measurements in Local Coordinate Frames

In this paper,the entrapping control problem of discrete-time AUVs with local coordinate frames is studied.To achieve entrapment in arbitrarily shaped orbits and formations,we design a bearingbased leader-following framework fully in the discrete-time domain with four parts:the orientation estimation unit,estimator unit,controller unit and parameters tuning unit.With bearing measurements and communication information,the orientation estimation unit can estimate orientations of local coordinate frames infinite time,and the estimator unit can achieve local localization.Based on estimation,the controller unit can drive each AUV to track the desired orbit or formation with an arbitrary shape.We present su±cient conditions under which stability of the overall system is proved using the theorem offinite-time stability and LaSalle's theorem for the discrete-time system.Moreover,the parameters tuning unit can calculate optimal parameters to improve overall performance.Additionally,we extend our schemes to nonholonomic AUVs with unicycle models.Finally,simulation results demonstrate the effectiveness of the proposed scheme.

2-D distributed pose estimation of multi-agent systems using bearing measurements

This article studies distributed pose(orientation and position)estimation of leader–follower multi-agent systems over𝜅-layer graphs in 2-D plane.Only the leaders have access to their orientations and positions,while the followers can measure the relative bearings or(angular and linear)velocities in their unknown local coordinate frames.For the orientation estimation,the local relative bearings are used to obtain the relative orientations among the agents,based on which a distributed orientation estimation algorithm is proposed for each follower to estimate its orientation.For the position estimation,the local relative bearings are used to obtain the position constraints among the agents,and a distributed position estimation algorithm is proposed for each follower to estimate its position by solving its position constraints.Both the orientation and position estimation errors converge to zero asymptotically.A simulation example is given to verify the theoretical results.