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Multilevel modeling and control of dynamic systems.

Victoria Erofeeva1, Oleg Granichin2, Renata Avros3

  • 1St. Petersburg State University, 7-9 Universitetskaya Embankment, St. Petersburg, 199034, Russia. v.erofeeva@spbu.ru.

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Summary
This summary is machine-generated.

This study introduces a meso-scale framework for analyzing complex dynamic systems, offering a balanced approach to control strategies. This multiscale perspective enhances understanding and management of intricate system behaviors.

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Area of Science:

  • Systems Science
  • Control Theory
  • Robotics

Background:

  • Complex dynamic systems involve interdependent components with nonlinear interactions, making individual part analysis insufficient for prediction.
  • Technological advancements enable real-time monitoring and control of systems, even during transient processes.
  • Traditional system modeling uses micro-scale and macro-scale approaches, particularly in networked control and multi-agent systems.

Purpose of the Study:

  • To present a formal meso-level framework for depicting dynamics and control in complex systems.
  • To define integral characteristics and dynamics of clusters for simplified control synthesis.
  • To address model errors arising from changing cluster structures in dynamic systems.

Main Methods:

  • Development of a multiscale framework incorporating micro, meso, and macro-scale perspectives.
  • Formal meso-level depiction of dynamics and control based on stable attractors.
  • Definition of integral characteristics and cluster dynamics for control synthesis.
  • Application of the framework to robotic control tasks.

Main Results:

  • The meso-scale perspective balances detailed component analysis with overall system behavior.
  • Defined integral characteristics and cluster dynamics simplify control synthesis.
  • The framework demonstrates scalability and effectiveness in robotic control tasks.
  • The approach addresses model errors from dynamic cluster structures.

Conclusions:

  • The proposed meso-level framework provides a powerful tool for understanding and managing complex dynamic systems.
  • Leveraging the meso-scale perspective enhances the efficiency and effectiveness of operational strategies.
  • This approach offers scalable and effective control strategies for applications like multi-robot systems.