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Design of quadcopter attitude controller based on data-driven model-free adaptive sliding mode control

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Abstract

In this paper, a four-rotor aircraft model-free adaptive sliding mode control (MFASMC) approach is suggested. This approach can eliminate the four-rotor model dependence of the model-based control approach. Only the UAV system’s input and output data are used to tackle the tricky dynamic modeling and parameter identification issues. The technique separates the quadrotor’s attitude control process into two phases: The sliding mode control algorithm is introduced in the outer-loop position control design to lessen the impact of outside disturbances on the system’s robust performance and to provide an internal reference attitude angle. The compact format dynamic linearization data model is equivalent to the attitude control of the inner loop. A model-free adaptive sliding mode attitude controller (MFASMC) is created using the data model to ensure quick convergence of the attitude angle. A disturbance observer is also added to the position controller to rectify the measured disturbance and prevent it from interfering with the position information feedback control. The Lyapunov approach is then used to demonstrate the system’s stability, and in the presence of model uncertainty and outside disturbance, the asymptotic convergence of the controller’s tracking error is ensured. Finally, numerical simulation is used to confirm the efficiency of the method and the viability of the plan. The experimental results show that compared with GA algorithm, PSO-RBF algorithm and PID algorithm, the error of the improved MFASMC algorithm is reduced by about 1.19%, 2.11% and 6.95%, respectively. Therefore, the model-free adaptive sliding mode attitude control method designed in this paper has high stability and accuracy when it does not depend on the dynamic model of the aircraft.

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Data availability

The data used to support the findings of this study are available from the corresponding author upon request.

Abbreviations

PID:

Proportional integral derivative

SMC:

Sliding mode control

MFASMC:

Model-free adaptive sliding mode attitude control

DOB:

Disturbance observer

GA:

Genetic algorithm

PSO-RBF:

Particle swarm optimization radial basis function

UAV:

Unmanned air vehicle

CFDL:

Compact format dynamic linearization

MIMO:

Multi-input multi-output

ADRC:

Active disturbance rejection control

LQR:

Linear quadratic regulator

LQG:

Linear Quadratic Gaussian

MPC:

Model predictive control

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Acknowledgements

The authors are grateful to Jiangxi University of Science and Technology for its help.

Funding

This work is partially supported by Jiangxi Provincial National Science Foundation (No. 20202BAL202009).

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Authors and Affiliations

  1. School of Electronic Automation, Jiangxi University of Science and Technology, Ganzhou, 341000, China

    Ding Yongjun, Wang Jianhong, Zhang Jinlong & Luo Xi

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  1. Ding Yongjun
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  2. Wang Jianhong
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  3. Zhang Jinlong
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  4. Luo Xi
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Contributions

This paper is written by the first author. The second author modifies the paper. The third author provides support and help for the experimental simulation of the article.

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Correspondence to Ding Yongjun.

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Yongjun, D., Jianhong, W., Jinlong, Z. et al. Design of quadcopter attitude controller based on data-driven model-free adaptive sliding mode control. Int. J. Dynam. Control 12, 1404–1414 (2024). https://doi.org/10.1007/s40435-023-01281-8

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