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Data-driven trajectory tracking control of UAV systems under a novel probability-selection event-triggered mechanism
Chao Cheng1, Haotong Lv2, Wenxin Sun3
1School of Computer Science and Engineering, Changchun University of Technology, Changchun 130012, China.
ISA Transactions
|June 30, 2026
Summary
This study introduces a data-driven control for unmanned aerial vehicles (UAVs) using a probability-selection event-triggered mechanism (PETM). This method reduces communication load by optimizing data transmission for stable UAV trajectory tracking.
Area of Science:
- Robotics and Control Systems
- Aerospace Engineering
- Data-Driven Control
Background:
- Unmanned Aerial Vehicle (UAV) trajectory tracking requires efficient control strategies.
- Conventional event-triggered mechanisms (ETM) can lead to communication channel overload, especially in stable systems.
- Data-driven approaches offer potential for model-free control design.
Purpose of the Study:
- To develop a data-driven trajectory tracking control method for UAVs.
- To introduce a probability-selection event-triggered mechanism (PETM) to reduce communication load.
- To co-design the control system without explicit knowledge of UAV dynamics.
Main Methods:
- A two-phase PETM is proposed: initial triggering via ETM, followed by probability-based selection of the actual transmitted packet (ATP).
- A data-driven system representation is utilized.
- Stability is analyzed using linear matrix inequalities (LMIs).
- Co-design of the event-triggering matrix and controller gain is performed.
Main Results:
- The PETM effectively minimizes redundant packet transmissions as the UAV system approaches stability.
- A data-driven stability criterion is established.
- The co-design approach successfully balances system performance and signal transmission rate.
- An illustrative example confirms the method's effectiveness for UAV trajectory tracking.
Conclusions:
- The proposed data-driven control with PETM enhances communication efficiency for UAV trajectory tracking.
- The method achieves robust control without needing precise UAV dynamic models.
- This approach is suitable for alleviating communication overload in UAV systems.
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