Szczegóły publikacji
Opis bibliograficzny
Robust adaptive cooperative control of aerial agents under heterogeneous time-varying communication delays / Masoud Hajimani, Farhad Bayat, Saleh Mobayen, Milad Gholami, Paweł SKRUCH // Ain Shams Engineering Journal ; ISSN 2090-4479 . — 2026 — vol. 17 iss. 9 art. no. 104317, s. 1–19. — Bibliogr. s. 18–19, Abstr. — Publikacja dostępna online od: 2026-07-01
Autorzy (5)
- Hajimani Masoud
- Bayat Farhad
- Mobayen Saleh
- Gholami Milad
- AGHSkruch Paweł
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 169052 |
|---|---|
| Data dodania do BaDAP | 2026-07-31 |
| Tekst źródłowy | URL |
| DOI | 10.1016/j.asej.2026.104317 |
| Rok publikacji | 2026 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Creative Commons | |
| Czasopismo/seria | Ain Shams Engineering Journal |
Abstract
In this work, we developed a distributed method for three-dimensional formation control of fixed-wing UAVs that is both robust and energy-efficient. The practical challenge is that the UAVs have to deal with time-varying communication delays (TVCD) that are different for each vehicle, but most existing methods either oversimplify or ignore this. We proposed a novel non-singular adaptive integral sliding mode controller (ISMC) that eliminates chattering and rejects disturbances in finite time, which improves tracking accuracy and reduces control effort. Then, a consensus protocol is designed on an undirected graph where not every UAV has direct access to the leader’s states, and it handles those varying delays properly. We proved the whole system is globally uniformly asymptotically stable (GUAS) using Lyapunov–Krasovskii analysis. Moreover, an LMI-based synthesis is given for computing a clear bound on how much delay the system can tolerate for large-scale applications. Also, the reference trajectories are generated using a hybrid MPC-PCHIP method that can produce aggressive maneuvers like sharp turns and obstacle avoidance while respecting velocity and acceleration limits in practice. Comparative high-fidelity simulations on a realistic nonlinear UAV model with aerodynamic coupling showed that our approach tracks better, rejects disturbances more effectively, and uses less control effort across different delay scenarios and challenging paths. Sensitivity tests also confirmed that the method is resilient to measurement noise and parameter errors, which makes it suitable for complex missions like wildfire monitoring.
