Global adaptive coordinated control of human–robot mooring system without velocity measurements

In this paper, a novel decentralized adaptive coordinated control approach is proposed for human–robot mooring system (HRMS) under the communication topology of the network. First, to achieve output feedback control of multiple robots and ensure uniform, exponential, and global convergence of estimation errors, a distributed filter is proposed for HRMS to eliminate the need for velocity measurement information. Then, instead of modifying the control structure, a universal time-varying asymmetric barrier function (UTABF) is designed to directly confine the system output. It can handle both constrained and unconstrained instances equally. Moreover, adaptive neural networks (NNs) backstepping controllers are proposed to handle the nonlinearities and uncertainties of the system dynamics. The goal of achieving globally uniformly ultimately bounded (GUUB) is achieved by introducing a switch function. Finally, simulation experiments of HRMS composed of a ship model (60,000DWT bulk carrier) are provided to verify the effectiveness of the proposed control algorithms.