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Control systems are everywhere in contemporary society, influencing diverse applications from aerospace to automated manufacturing. These systems can be found naturally within biological processes, such as blood sugar regulation and heart rate adjustment in response to stress, as well as in man-made systems like elevators and automated vehicles. A control system is essentially a network of subsystems and processes that collaboratively convert specific inputs into desired outputs.
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The transfer function is a fundamental concept in the analysis and design of linear time-invariant (LTI) systems. It offers a concise way to understand how a system responds to different inputs in the frequency domain. It serves as a bridge between the time-domain differential equations that describe system dynamics and the frequency-domain representation that facilitates easier manipulation and analysis.
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Formation-containment control of networked Euler-Lagrange systems: An event-triggered framework.

Liangming Chen1, Chuanjiang Li1, Bing Xiao2

  • 1Department of Control Science and Engineering, Harbin Institute of Technology, Harbin, 150001, China.

ISA Transactions
|November 12, 2018
PubMed
Summary
This summary is machine-generated.

This study introduces an event-triggered control framework for networked Euler-Lagrange systems, enabling leaders to form configurations and followers to achieve containment. This approach reduces communication load while handling system uncertainties.

Keywords:
Euler–Lagrange systemEvent-triggeredFormation-containmentNetworked systems

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Area of Science:

  • Robotics and Control Systems
  • Networked Systems Engineering
  • Applied Mathematics

Background:

  • Designing simultaneous formation and containment controllers for networked systems is challenging.
  • Existing methods often require extensive communication and relative velocity information.

Purpose of the Study:

  • To develop an event-triggered control framework for networked Euler-Lagrange systems.
  • To achieve formation control for leaders and containment control for followers concurrently.
  • To reduce communication burden and handle parametric uncertainties.

Main Methods:

  • An event-triggered formation controller for leader configuration.
  • An event-triggered containment control law for follower convergence to the leader's convex hull.
  • Adaptive gain tuning using local information and adaptive updating laws for uncertainties.
  • Exclusion of Zeno behaviors in triggering sequences.

Main Results:

  • Successfully achieved concurrent formation and containment control.
  • Eliminated the need for relative velocity information among followers.
  • Adaptive control effectively managed parametric uncertainties.
  • Demonstrated reduced communication burden through event-triggered updates.
  • Numerical simulations validated the framework's effectiveness.

Conclusions:

  • The proposed event-triggered framework offers an efficient solution for formation-containment control in networked systems.
  • Adaptive control and event-triggered mechanisms enhance robustness and reduce communication overhead.
  • The method is effective even with parametric uncertainties and avoids Zeno phenomena.