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This paper studies the congestion control problem of multiple bottleneck networks. First, this paper regards the routing nodes of the network as multi-agents, and considers its own dynamic process. For the first time, the time-varying characteristics of the number of sessions in the network transmission process and the mutual influence between nodes are considered into the model, and a queue utilization rate switching model is established to describe the dynamics of a single agent. Then, considering the boundedness of the control input, combined with the prescribed performance technique, two congestion controllers are designed by using the backstepping method according to whether the controller depends on the number of sessions. The designed congestion controllers improve the robustness of the TCP/AQM network system in the case of frequent and time-varying sessions in multiple bottleneck networks. In addition, the designed controllers can stabilize different routing nodes of multiple bottleneck networks under different queue lengths, thereby improving the utilization efficiency of the network. Finally, the effectiveness and superiority of the designed controllers are verified by simulation. • TCP/IP network node queue utilization switching model is built. • The controller design takes into account the input saturation characteristics. • Two prescribed performance congestion control algorithms are designed. [ABSTRACT FROM AUTHOR]

In this paper, a performance constraint control problem is considered for Transmission Control Protocol/Active Queue Management (TCP/AQM) network with external disturbance and input saturation. On the basis of backstepping-like design procedure and fuzzy approximation technique, an adaptive fuzzy controller with prescribed constraint is achieved to ensure that the transient and steady state performances of the tracking errors can be satisfied. The stability analysis proves that all the signals in the closed-loop system are semi-globally, uniformly and ultimately bounded. The simulation results clarify the feasibility and effectiveness of the proposed approach. • A new generalized AIMD network model with input saturation and external disturbances is proposed by combining the two existing models for Transmission Control Protocol/Active Queue Management (TCP/AQM) network. • A novel congestion control method is presented to solve a tracking problem by using funnel control, adaptive backstepping, and fuzzy logic systems. • The steady and transient state performances of the tracking error can satisfy the design requirements. [ABSTRACT FROM AUTHOR]

The congestion control problem of TCP network systems with user datagram protocol (UDP) flows is investigated in this paper. A nonlinear TCP network model with strict-feedback structure is first established. The unknown UDP flow is regarded as the external disturbance, and the maximum UDP flow is calculated by using the minimax approach. And then, a congestion control algorithm is proposed by using the adaptive backstepping approach. Meanwhile, the adaptive law is employed to estimate the unknown link capacity. The design of the adaptive law is to introduce a parameter mapping mechanism to limit the parameter identification range to a specified interval, thereby improving the estimation efficiency of the parameters. Furthermore, a state-feedback congestion controller is presented to make sure that the output of the system tracks the desired queue. The simulation results show the superiority and feasibility of the proposed method. • The UDP flow is addressed by the minimax method instead of H ∞ control. • A novel congestion algorithm is presented to solve an adaptive tracking problem. • The steady-state error of the closed-loop system satisfies the design requirements. [ABSTRACT FROM AUTHOR]

An H ∞ congestion tracking control problem for nonlinear transmission control protocol/active queue management (TCP/AQM) network is proposed in this paper. Inspired by the existing network models, a modified TCP/AQM network model with external disturbance and modelling uncertainty is first introduced. And then, a novel function for the desired queue length is defined for the first time, which can simulate the changes in the queue length during a day. Next, a novel AQM scheme is presented to control network congestion by combining H ∞ theory and integral backstepping technique. The proposed method guarantees that the better tracking performance of the queue is achieved, and all the signals are asymptotically stable in the closed-loop system in probability. Finally, the effectiveness of the presented algorithm is tested by simulation results. [ABSTRACT FROM AUTHOR]

This paper extends the well-known control method, prescribed performance control (PPC), to network congestion control problems. An adaptive H ∞ tracking problem for Transmission Control Protocol/Active Queue Management (TCP/AQM) system with external disturbance is studied. Firstly, a modified network model is given. And then, the model is changed to an equivalent error model by using error transformation. Next, to solve the network congestion problem, prescribed performance, backstepping technique, adaptive control and H ∞ control are combined to design a congestion controller. Due to the use of prescribed performance, the controller can guarantee both the transient and steady state performance of the system. Meanwhile, the output of the system can track the desired queue, and unknown link capacity can be estimated. Finally, a simulation result is shown to clarify the feasibility and effectiveness of proposed approach. [ABSTRACT FROM AUTHOR]