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Coordinated decentralized adaptive output feedback control of interconnected systems.

Naira Hovakimyan1, Eugene Lavretsky, Bong-Jun Yang

  • 1Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA. nhovakim@vt.edu

IEEE Transactions on Neural Networks
|March 1, 2005
PubMed
Summary

This study introduces a decentralized adaptive control method for large interconnected systems using neural networks to manage system interconnections and ensure stable performance. The approach guarantees bounded error signals for improved tracking accuracy.

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Area of Science:

  • Control Engineering
  • Systems Science
  • Artificial Intelligence

Background:

  • Large-scale interconnected systems present significant control challenges due to complex interdependencies.
  • Achieving robust tracking performance in such systems requires advanced control strategies.
  • Existing methods may struggle with the dynamic nature and scale of these systems.

Purpose of the Study:

  • To design a decentralized adaptive output feedback control strategy for large-scale interconnected systems.
  • To mitigate the impact of interconnections on system tracking performance.
  • To ensure the stability and boundedness of error signals within the control framework.

Main Methods:

  • A decentralized adaptive control architecture is proposed.

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  • Linearly parameterized neural networks are employed for each subsystem.
  • Lyapunov's direct method is utilized to prove signal boundedness.

    • Main Results:

    • The proposed control design effectively manages interconnections.
    • Partial cancellation of interconnection effects on tracking performance is achieved.
    • The boundedness of error signals is rigorously demonstrated.

    Conclusions:

    • The developed decentralized adaptive control is effective for large-scale interconnected systems.
    • The use of neural networks offers a viable approach for handling system interconnections.
    • The control strategy ensures system stability and reliable tracking performance.