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Output Feedback Adaptive Dynamic Surface Sliding-Mode Control for Quadrotor UAVs with Tracking Error Constraints

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  • Guoqiang Zhu
  • Sen Wang
  • Lingfang Sun
  • Weichun Ge
  • Xiuyu Zhang

Abstract

In this paper, a fuzzy adaptive output feedback dynamic surface sliding-mode control scheme is presented for a class of quadrotor unmanned aerial vehicles (UAVs). The framework of the controller design process is divided into two stages: the attitude control process and the position control process. The main features of this work are (1) a nonlinear observer is employed to predict the motion velocities of the quadrotor UAV; therefore, only the position signals are needed for the position tracking controller design; (2) by using the minimum learning technology, there is only one parameter which needs to be updated online at each design step and the computational burden can be greatly reduced; (3) a performance function is introduced to transform the tracking error into a new variable which can make the tracking error of the system satisfy the prescribed performance indicators; (4) the sliding-mode surface is introduced in the process of the controller design, and the robustness of the system is improved. Stability analysis proved that all signals of the closed-loop system are uniformly ultimately bounded. The results of the hardware-in-the-loop simulation validate the effectiveness of the proposed control scheme.

Suggested Citation

  • Guoqiang Zhu & Sen Wang & Lingfang Sun & Weichun Ge & Xiuyu Zhang, 2020. "Output Feedback Adaptive Dynamic Surface Sliding-Mode Control for Quadrotor UAVs with Tracking Error Constraints," Complexity, Hindawi, vol. 2020, pages 1-23, June.
    • Handle: RePEc:hin:complx:8537198
    DOI: 10.1155/2020/8537198
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    Cited by:

    1. Hossein Moayedi & Amir Mosavi, 2021. "Electrical Power Prediction through a Combination of Multilayer Perceptron with Water Cycle Ant Lion and Satin Bowerbird Searching Optimizers," Sustainability, MDPI, vol. 13(4), pages 1-18, February.
    2. Hossein Moayedi & Amir Mosavi, 2021. "Synthesizing Multi-Layer Perceptron Network with Ant Lion Biogeography-Based Dragonfly Algorithm Evolutionary Strategy Invasive Weed and League Champion Optimization Hybrid Algorithms in Predicting He," Sustainability, MDPI, vol. 13(6), pages 1-20, March.
    3. Hossein Moayedi & Amir Mosavi, 2021. "Double-Target Based Neural Networks in Predicting Energy Consumption in Residential Buildings," Energies, MDPI, vol. 14(5), pages 1-25, March.
    4. Hossein Moayedi & Amir Mosavi, 2021. "An Innovative Metaheuristic Strategy for Solar Energy Management through a Neural Networks Framework," Energies, MDPI, vol. 14(4), pages 1-18, February.

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