Adaptive neural practically finite-time congestion control for TCP/AQM network

Inspired by the prescribed performance control (PPC), a new performance function, called finite-time performance function (FTPF), is first defined in this paper, by which a novel finite-time control design process is introduced. This work is also the first to solve the finite-time control issue for a class of transmission control protocol/active queue management (TCP/AQM) networks. Meanwhile, with the aid of FTPF, PPC and neural networks, a new adaptive practically pre-assigned finite-time controller is designed, which guarantees that the queue length q(t) tracks the desired queue q(ref) in finite-time and all the signals of the closed-loop system are semi-globally practical finite-time stable (SGPFS). Finally, simulation results are shown to illustrate the effectiveness of the proposed method. (C) 2019 Elsevier B.V. All rights reserved.