Global Sensitive-Based Input Shaping for UAV-Payload Precision Motion Control

2026-07-29

AI Summary

This work addresses the challenge of achieving high-precision control in unmanned aerial vehicle (UAV) slung-load systems under uncertainties in payload mass and cable length. The authors propose an uncertainty-aware robust control framework that, for the first time, incorporates the Shapley value into input shaper design. By integrating global sensitivity analysis, the method systematically quantifies the influence of parametric uncertainties on system response and constructs an input shaping strategy with reduced sensitivity to these variations. This approach synergistically combines input shaping with robust control, substantially diminishing the controller’s reliance on precise knowledge of uncertain parameters. Simulation results demonstrate that the proposed framework outperforms non-robust, conventional robust, and minimax approaches in terms of both stability and trajectory tracking accuracy under parameter uncertainty.

Abstract

This work presents a comprehensive analysis and design of global sensitivity-based input shapers for a 3D Unmanned Aerial Vehicle-payload system, emphasizing robustness against uncertainties in payload mass and rope length. The proposed approach also leverages the Shapley value concept in controller design to systematically account for uncertainties, thereby reducing the controller's sensitivity to unknown parameters. To validate the effectiveness of the methodology, numerical simulations are conducted, comparing the proposed controller against non-robust, robust, and minimax designs. The results demonstrate that the standard global sensitivity or Shapley-based input shapers improve performance and offer a promising framework for uncertainty-aware control in aerial payload transport.

Problem

• UAV-payload system
• precision motion control
• parameter uncertainty
• input shaping
• robustness

Innovation

• global sensitivity
• input shaping
• Shapley value
• UAV-payload system
• robust control