Hamiltonian theory applied to ameliorate the complexity of tcp network congestion control
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KünyeWang, K., Jing, Y., Zhang, S., Dimirovski, G. M. (2017). Hamiltonian theory applied to ameliorate the complexity of tcp network congestion control. In 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC) (pp. 2579-2584). https://doi.org/10.1109/SMC.2017.8123013
An active queue management controller based on Hamiltonian energy theory for a class of nonlinear TCP network congestion system in the presence of uncertain parameters and unknown external disturbances is derived. The restriction of inequality assumption is eliminated by introducing the MiniMax methods into dissipation Hamilton system. Sufficient conditionsfor the existence of MiniMax controller under circumstances the network system is attacked with maximum impact disturbance has been derived via Lyapunov stability theory. Furthermore, the nonlinear uncertainties presence is successfully ameliorated by employing a parameter projection mechanism. Simulation experiments have demonstrated this energy based control strategy ameliorates the pertinent control complexity and is considerably more effective in improving both transient stability and robustness.