A Novel Connectivity-Preserving Control Design for Rendezvous Problem of Networked Uncertain Nonlinear Systems

Distributed Path Following of Multiple Under-Actuated Autonomous Surface Vehicles Based on Data-Driven Neural Predictors via Integral Concurrent Learning

This article addresses the problem of distributed path following of multiple under-actuated autonomous surface vehicles (ASVs) with completely unknown kinetic models. An integrated distributed guidance and learning control architecture is proposed for achieving a time-varying formation. Specifically, a robust distributed guidance law at the kinematic level is developed based on a consensus approach, a path-following mechanism, and an extended state observer. At the kinetic level, a model-free kinetic control law based on data-driven neural predictors via integral concurrent learning is designed such that the kinetic model can be learned by using recorded data. The advantage of the proposed method is two-folds. First, the proposed formation controllers are able to achieve various time-varying formations without using the velocities of neighboring vehicles. Second, the proposed control law is model-free without any parameter information on kinetic models. Simulation results substantiate the effectiveness of the proposed robust distributed guidance and model-free control laws for multiple under-actuated ASVs with fully unknown kinetic models.

Cooperative Output Regulation Problem of Nonlinear Multiagent Systems With Proximity Graph via Output Feedback Control

This article considers the cooperative output regulation problem of nonlinear output feedback systems under the communication network modeled by the proximity graph, which is time varying and state dependent. Under the relaxed assumption that the proximity graph is initially connected, based on an improved potential function, we first propose a distributed connectivity-preserving output feedback control law with a linear internal model and distributed observer, which is robust to uncertain parameter and external disturbances in heterogeneous subsystems with strong nonlinearity. Successively, an adaptive design with parameter update law is derived to further tolerate an uncertain parameter in the exosystem, which generates the leader's trajectory and external disturbances.