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Related Experiment Videos

Adaptive backstepping H∞ tracking control with prescribed performance for internet congestion.

Yang Liu1, Xiaoping Liu2, Yuanwei Jing3

  • 1College of Information Science and Engineering, Northeastern University, Shenyang 110819, Liaoning, PR China; Department of Electrical Engineering, Lakehead University, Thunder Bay, Ontario, Canada P7B 5E1.

ISA Transactions
|October 29, 2017
PubMed
Summary

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This study introduces prescribed performance control (PPC) for network congestion control, enhancing Transmission Control Protocol/Active Queue Management (TCP/AQM) systems. The new adaptive H∞ controller ensures system stability and tracks desired queue lengths effectively.

Area of Science:

  • Control Theory
  • Computer Networks
  • Adaptive Systems

Background:

  • Network congestion impacts performance in TCP/AQM systems.
  • External disturbances pose challenges to stable network control.
  • Prescribed Performance Control (PPC) is a known method for system performance guarantees.

Purpose of the Study:

  • To adapt Prescribed Performance Control (PPC) for network congestion control.
  • To address adaptive H∞ tracking in TCP/AQM systems under disturbance.
  • To design a controller guaranteeing transient and steady-state performance.

Main Methods:

  • Modified network modeling and error transformation.
  • Combined application of PPC, backstepping, adaptive control, and H∞ control.
  • Development of a novel congestion controller.
Keywords:
Adaptive H∞ tracking controlBackstepping techniquePrescribed performance controlTCP/AQM system

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Main Results:

  • The controller ensures both transient and steady-state performance.
  • The system successfully tracks the desired queue length.
  • Unknown link capacity is accurately estimated.
  • Simulation validates the approach's feasibility and effectiveness.

Conclusions:

  • The proposed controller effectively manages network congestion.
  • PPC integration enhances TCP/AQM system performance.
  • The method offers a robust solution for adaptive H∞ tracking problems.