Model Predictive Control-Based Trajectory Planning for a Stewart Platform: Planning and Tracking for UAV Capture Using Parallel Manipulator System

Posluszny, Michal Antoni ; Jensen, Rasmus ; Fogh, Anders Henriksen

4. semester

Sustainable Energy Engineering, Master

2025

2025-06-02

104 pages

The focus of this project is the development of a trajectory planning and tracking system for the Stewart platform, as part of an active UAV retrieval strategy aiming to improve the landing safety in autonomous UAV operations. The complete strategy involves predict- ing the UAV trajectory and tracking it with a Stewart platform to allow for the retrieval of UAVs following arbitrary trajectories. The developed planning system for the Stewart platform employs an MPC controller, ensuring the planned trajectories are dynamically feasible and safe to execute for the Stewart platform, based on the dynamic model and operational constraints defined for the platform. The planned trajectory tracking is en- abled by a dedicated tracking controller using the full-state reference provided by the MPC. The system was implemented in Simulink® and validated experimentally on a physi- cal setup, which was able to accurately track the generated UAV trajectory supplied to the planning system. The system demonstrated a consistent performance, leading to a successful retrieval of the UAV within the defined error margins, in a range of assessed scenarios. However, ensuring strict adherence to the specified workspace envelope pre- sented a limitation to the system’s reliability. Further validation of the planning frame- work in more demanding testing conditions is required to assess the applicability of the system to high-speed UAV retrieval.

The focus of this project is the development of a trajectory planning and tracking system for the Stewart platform, as part of an active UAV retrieval strategy aiming to improve the landing safety in autonomous UAV operations. The complete strategy involves predict- ing the UAV trajectory and tracking it with a Stewart platform to allow for the retrieval of UAVs following arbitrary trajectories. The developed planning system for the Stewart platform employs an MPC controller, ensuring the planned trajectories are dynamically feasible and safe to execute for the Stewart platform, based on the dynamic model and operational constraints defined for the platform. The planned trajectory tracking is en- abled by a dedicated tracking controller using the full-state reference provided by the MPC. The system was implemented in Simulink® and validated experimentally on a physi- cal setup, which was able to accurately track the generated UAV trajectory supplied to the planning system. The system demonstrated a consistent performance, leading to a successful retrieval of the UAV within the defined error margins, in a range of assessed scenarios. However, ensuring strict adherence to the specified workspace envelope pre- sented a limitation to the system’s reliability. Further validation of the planning frame- work in more demanding testing conditions is required to assess the applicability of the system to high-speed UAV retrieval.

MPC ; Trajectory Tracking ; Trajectory Planning ; Model Predictive Control ; Stewart Platform ; Parallel Manipulator ; Robotics ; UAV ; Advanced Control ; Workspace Envelope ; Optimization ; UAV Retrieval ; Forward Kinematics ; Inverse Kinematics ; 6 DOF ; Full-State Feedback ; State-Space ; Dynamic Modeling ; Parameter Estimation

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