Wayset-based guidance of multirotor aerial vehicles using robust tube-based model predictive control

Area of Science:

• Robotics
• Control Systems Engineering
• Aerospace Engineering

Background:

• Underactuated multirotor aerial vehicles (MAVs) present unique guidance challenges due to limited control inputs.
• Existing methods may struggle with robustly navigating complex trajectories while respecting operational constraints.

Purpose of the Study:

• To develop a robust wayset-based guidance system for underactuated MAVs.
• To enable MAVs to visit a sequence of waypoints, respecting state and control bounds, and allowing dwell times.

Main Methods:

• A hierarchical guidance and control structure with a supervisory guidance loop.
• Fixed-horizon tube-based robust model predictive control (MPC) for outer-loop guidance.
• Utilizing a reduced-order, discrete-time linear state-space model with bounded disturbances.

Main Results:

• Analytical proofs of MPC recursive feasibility, robust stability, and overall guidance feasibility.
• Numerical evaluation using a realistic quadrotor model demonstrated the method's effectiveness.
• The proposed MPC successfully guided the MAV through specified waysets while adhering to constraints.

Conclusions:

• The developed wayset-based MPC offers a robust and feasible solution for underactuated MAV guidance.
• The method ensures safe and efficient trajectory following with specified dwell times.
• This approach enhances the operational capabilities of MAVs in complex missions.