Integral adaptive event-triggered predefined-time control for robotic teleoperation systems

Area of Science:

• Robotics
• Control Systems Engineering
• Networked Systems

Background:

• Robotic teleoperation systems face challenges with limited communication bandwidth, impacting tracking performance.
• Existing control strategies often require frequent data transmission, leading to inefficient communication.
• Accurate position tracking is crucial for effective human-robot interaction in teleoperation.

Purpose of the Study:

• To develop an integral adaptive event-triggered control strategy for improving communication efficiency and tracking accuracy in robotic teleoperation.
• To reduce the communication network access frequency by intelligently triggering data updates.
• To ensure precise position tracking between master and slave robots within a predefined time.

Main Methods:

• An integral adaptive event-triggered mechanism was designed to evaluate error integrals for data update decisions.
• A predefined-time sliding mode controller was implemented using data transmitted at triggering moments.
• System stability was rigorously proven using theoretical analysis.
• The proposed strategy's effectiveness was validated through extensive simulations.

Main Results:

• The integral adaptive event-triggered mechanism significantly reduced communication network access frequency.
• The predefined-time sliding mode controller achieved accurate position tracking between master and slave robots.
• The overall system demonstrated proven stability.
• Simulations confirmed the superiority of the proposed strategy over existing methods.

Conclusions:

• The proposed integral adaptive event-triggered control strategy effectively enhances communication efficiency in robotic teleoperation.
• The strategy ensures accurate position tracking, with errors converging within a predefined time.
• This approach offers a significant reduction in information transmission for networked robotic systems.