Distributed formation control of multi-four-rotor UAVs using fractional-order robust sliding mode trajectory tracking
This paper proposes a fractional-order fast integral terminal sliding mode distributed formation control strategy for quadrotor UAV formations under actuator faults, wind disturbances, and other issues, based on an improved extended state observer (IESO). First, actuator faults, wind disturbances, and coupling effects encountered by the formation system are considered as lumped disturbances, which are effectively estimated using the improved extended state observer. Compared to the traditional extended state observer (ESO), the IESO introduces the GALN function to dynamically adjust the observer gain, thereby enhancing the system’s ability to respond to rapidly changing disturbances and significantly improving its robustness and response speed. Next, the estimated disturbance information is input into the fractional-order fast integral terminal sliding mode controller to compensate for the impact of disturbances on the system, ensuring that the formation system converges and tracks the desired signal rapidly within a finite time. Moreover, the proposed control strategy only relies on information exchange between neighboring UAVs, reducing dependence on global data and thus alleviating communication bandwidth pressure. To address the chattering problem in sliding mode control, a continuous function with relay characteristics is used to replace the traditional saturation function, achieving smooth control. Through rigorous mathematical proof, it is shown that the designed controller guarantees that the tracking error of the formation system will ultimately converge to zero. Finally, simulation comparisons with other control algorithms demonstrate that the proposed control algorithm achieves the smallest tracking error and the strongest robustness.
Authors
- Jun Wang (ORCID: https://orcid.org/0000-0003-0416-2325)
- Mingmin Luo (ORCID: https://orcid.org/0009-0007-2175-920X)
Institutions
- Lanzhou University of Technology (CN)
Publication Details
- Journal
- Transactions of the Institute of Measurement and Control
- Published
- 2025-09-16
- DOI
- https://doi.org/10.1177/01423312251351707
- Primary Topic
- Adaptive Control of Nonlinear Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00