| Keyword search (4,164 papers available) | ![]() |
"Adaptive control" Keyword-tagged Publications:
| Title | Authors | PubMed ID | |
|---|---|---|---|
| 1 | A type-3 fuzzy synchronization system subjected to hysteresis quantizer inputs and unknown dynamics: Applicable to financial and physical chaotic systems | Tian M; Mohammadzadeh A; Taghavifar H; Sakthivel R; Zhang C; | 41381323 ENCS |
| 2 | Distributed adaptive fault-tolerant cooperative control for fixed-wing UAVs with actuator faults and input constraints | Fu M; Yu Z; Zhang Y; | 40946062 ENCS |
| 3 | Nonsingleton Gaussian type-3 fuzzy system with fractional order NTSMC for path tracking of autonomous cars | Taghavifar H; Mohammadzadeh A; Zhang W; Zhang C; | 38160078 ENCS |
| Title: | Distributed adaptive fault-tolerant cooperative control for fixed-wing UAVs with actuator faults and input constraints | ||||
| Authors: | Fu M, Yu Z, Zhang Y | ||||
| Link: | https://pubmed.ncbi.nlm.nih.gov/40946062/ | ||||
| DOI: | 10.1016/j.isatra.2025.08.049 | ||||
| Publication: | ISA transactions | ||||
| Keywords: | Adaptive control; Fault-tolerant cooperative control; Fixed-wing unmanned aerial vehicle; Input constraints; | ||||
| PMID: | 40946062 | Category: | Date Added: | 2025-09-14 | |
| Dept Affiliation: |
ENCS
1 College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, Jiangsu, China. Electronic address: minruifu@nuaa.edu.cn. 2 College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, Jiangsu, China. Electronic address: yuziquan@nuaa.edu.cn. 3 Department of Mechanical, Industrial and Aerospace Engineering, Concordia University, Montreal, H3G 1M8, Quebec, Canada. Electronic address: youmin.zhang@concordia.ca. |
||||
Description: |
This paper proposes a distributed fault-tolerant cooperative control framework for multiple fixed-wing UAVs (FUAVs), grounded on a complete six-degrees-of-freedom (6-DOF) nonlinear dynamic model. The architecture integrates position and attitude control, explicitly accounting for actuator faults and multiple input constraints. In the outer loop, an adaptive proportional-derivative (PD) controller is implemented, with its gains optimized online via a model predictive control (MPC) strategy to handle time-varying constraints. The inner loop incorporates a fixed-time extended state observer (ESO) to estimate uncertainties and actuator degradation, combined with an online optimization mechanism to enforce actuator limits and enhance fault resilience. Uniform ultimate boundedness of tracking errors is formally guaranteed through Lyapunov analysis. Hardware-in-the-loop (HIL) simulations on a Pixhawk 6C autopilot, along with comparative studies against representative control strategies, demonstrate the proposed scheme's real-time feasibility and strong robustness under actuator faults and multiple input constraints. |



