Work

Nonlinear model predictive control trajectory tracking for a fixed-wing UAV in a deep-stall and perching landing maneuver with guaranteed stability

Year: 2025

Type: article

Abstract: We address the planning and control problems of a fixed-wing unmanned aerial vehicle (FW UAV) in a deep-stall and perching landing maneuver. We use optimal control methods to generate a trajectory that satisfies not only the aircraft maneuver requirement but also the recursive feasibility demands of the tracking control method that we use subsequently. To track the generated trajectory, we developed a Nonlinear Model Predictive Control (NMPC) scheme. We then outline the steps to systematically derive the NMPC terminal costs and the terminal sets tailored to this problem and formally prove the stability of the NMPC tracking scheme. Simulation results for different initial conditions show the viability of the developed scheme for the deep-stall and perching landing maneuvers. Finally, we examine the relationships between airspeed, wing loading, elevator deflection angle, and flight path angle in steady flight, including deep-stall landing.

Source: European Journal of Control

DOI: 10.1016/j.ejcon.2025.101442

Authors: Huu Thien Nguyen, Ionela Prodan, Fernando A.C.C. Fontes

Institutions: Universidade do Porto, Centro de Investigação em Sistemas e Tecnologias, Institut polytechnique de Grenoble, Laboratoire de Conception et d'Intégration des Systèmes, Université Grenoble Alpes

Language: English

Topic: Advanced Control Systems Optimization

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $2,850

Funders: Université Grenoble Alpes, Agence Nationale de la Recherche, Ministério da Ciência, Tecnologia e Ensino Superior, Fundação para a Ciência e a Tecnologia