Adaptive Ascent Control of a Collaborative Object Transportation System Using Two Quadrotors

Area of Science:

• Robotics and Control Systems
• Unmanned Aerial Vehicle (UAV) Systems
• Mechatronics

Background:

• Collaborative control of multiple Unmanned Aerial Vehicles (UAVs) is crucial for complex tasks like payload transportation.
• Traditional Position Feedback Controllers (PFC) for follower UAVs rely on GPS or leader UAV position, which can be unstable outdoors.
• Existing methods struggle with maintaining payload stability, especially under varying load conditions.

Purpose of the Study:

• To develop and validate a novel Force Feedback Controller (FFC) for outdoor collaborative control of two quadrotor UAVs (QDRs) transporting a long payload.
• To eliminate the need for leader QDR positional feedback and Global Positioning System (GPS) for the follower QDR.
• To introduce an adaptive mechanism for the FFC to manage varying payload masses and minimize horizontal payload displacement.

Main Methods:

• Implemented a leader-follower control strategy for two QDRs.
• Utilized conventional Proportional-Derivative (PD) controllers for the leader QDR trajectory tracking.
• Developed and applied a Force Feedback Controller (FFC) based on admittance control principles for the follower QDR, using contact force feedback.
• Designed an adaptive admittance controller that adjusts to payload mass variations.
• Simulated the adaptive FFC system in Matlab-Simulink.

Main Results:

• The adaptive FFC successfully controlled the follower QDR without relying on leader position or GPS data.
• The system demonstrated effective trajectory tracking and horizontal payload stabilization.
• The controller's performance remained robust across different payload mass variations.
• Minimized horizontal position differences between the two QDRs, enhancing payload stability.

Conclusions:

• The adaptive Force Feedback Controller (FFC) offers a robust solution for outdoor collaborative control of dual quadrotor UAV systems.
• This approach enhances payload transportation stability and accuracy, particularly in the presence of varying payload masses.
• The FFC eliminates reliance on GPS and leader position feedback, paving the way for more versatile UAV applications.