Finite-Time Attitude Fault Tolerant Control of Quadcopter System via Neural Networks
Abstract
:1. Introduction
- The NFTSMC method is used to enhance the convergence speed and robustness of the quadcopter system.
- The adaptive law is integrated with the NFTSMC to tackle the unknown external disturbances.
- Radial basic function neural networks (RBFNNs) are combined with adaptive laws to handle model uncertainties and actuator faults.
- The proposed control technique has several merits such as robustness, fast finite time convergence, handling model uncertainties and external disturbances, accommodating actuator faults, and lack of magnitude information of bounded faults.
2. Problem Formulation
2.1. Mathematical Tools
2.2. Nonsingular Fast Terminal Sliding Mode
2.3. Quadcopter Model
3. Flight Controller Design
3.1. Design of ANFTSMC
3.2. Synthetizing ANFTSMC with Neural Network
4. Simulation
4.1. Scenario 1
4.2. Scenario 2
4.3. Scenario 3
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
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Parameter | Description | Value |
---|---|---|
Arm length | ||
Thrust coefficient | ||
Drag coefficient | ||
Total mass | ||
Moments of inertia | ||
Rotor inertia |
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Nguyen, N.P.; Mung, N.X.; Thanh Ha, L.N.N.; Huynh, T.T.; Hong, S.K. Finite-Time Attitude Fault Tolerant Control of Quadcopter System via Neural Networks. Mathematics 2020, 8, 1541. https://doi.org/10.3390/math8091541
Nguyen NP, Mung NX, Thanh Ha LNN, Huynh TT, Hong SK. Finite-Time Attitude Fault Tolerant Control of Quadcopter System via Neural Networks. Mathematics. 2020; 8(9):1541. https://doi.org/10.3390/math8091541
Chicago/Turabian StyleNguyen, Ngoc Phi, Nguyen Xuan Mung, Le Nhu Ngoc Thanh Ha, Tuan Tu Huynh, and Sung Kyung Hong. 2020. "Finite-Time Attitude Fault Tolerant Control of Quadcopter System via Neural Networks" Mathematics 8, no. 9: 1541. https://doi.org/10.3390/math8091541
APA StyleNguyen, N. P., Mung, N. X., Thanh Ha, L. N. N., Huynh, T. T., & Hong, S. K. (2020). Finite-Time Attitude Fault Tolerant Control of Quadcopter System via Neural Networks. Mathematics, 8(9), 1541. https://doi.org/10.3390/math8091541