Optimizing Unmanned Air–Ground Vehicle Maneuvers Using Nonlinear Model Predictive Control and Moving Horizon Estimation

Autor: Alessandra Elisa Sindi Morando, Alessandro Bozzi, Simone Graffione, Roberto Sacile, Enrico Zero
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Automation, Vol 5, Iss 3, Pp 324-342 (2024)
Druh dokumentu: article
ISSN: 2673-4052
DOI: 10.3390/automation5030020
Popis: In this paper, Nonlinear Model Predictive Control (NMPC) and Nonlinear Moving Horizon Estimator (NMHE) are combined to control, in a distributed way, a heterogeneous fleet composed of a steering car and a quadcopter. In particular, the ground vehicle in the role of the leader communicates its one-step future position to the drone, which keeps the formation along the desired trajectory. Inequality constraints are introduced in a switching control fashion to the leader’s NMPC formulation to avoid obstacles. In the literature, few works using NMPC and NMHE deal with these two vehicles together. Moreover, the presented scheme can tackle noisy, partial, and missing measurements of the agents’ state. Results show that the ground car can avoid detected obstacles, keeping the tracking errors of both robots in the order of a few centimeters, thanks to trustworthy NMHE estimates and NMPC predictions.
Databáze: Directory of Open Access Journals