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For the nonlinear TCP/AWM network congestion control system with external disturbances, under the framework of backstepping control method, an adaptive network congestion control strategy based on event-triggered mechanism is proposed. This strategy reduces the waste of network resources by introducing an event-triggered mechanism and uses RBF neural network to deal with external disturbances. The Lyapunov theory is used to prove that all signals in the closed-loop system are bounded. Finally, the proposed method is verified by simulation and is compared with PID, which further verifies the effectiveness of the proposed control method. [ABSTRACT FROM AUTHOR]

This work investigates a finite-time H ∞ robust congestion control issue for transmission control protocol network systems. By means of the backstepping technique, finite-time control method and H ∞ control theory, a novel robust H ∞ finite-time controller design approach is presented to guarantee the finite-time convergence of the queue tracking error. Furthermore, the closed-loop network system has an L 2 gain less than or equal to a given positive real number. Comparative simulation results show that the proposed control method performs better than the existing control approach. [ABSTRACT FROM AUTHOR]

This work investigates an adaptive finite-time congestion control problem of transmission control protocol/active queue management. By means of the funnel control, neural networks and sliding mode control, a new AQM algorithm is proposed to ensure that the tracking error e 1 t converges to the prescribed boundary in finite time and the transient and steady-state performances of e 1 t can be satisfied. The stability analysis is given to prove that all the signals of the closed-loop system are finite-time bounded. Finally, a comparison example is considered to demonstrate the feasibility and superiority of the presented scheme. [ABSTRACT FROM AUTHOR]