Adaptive fuzzy gain-scheduling robust control for stability of quadrotors

• Published in: Applied mathematical modelling Vol. 138; p. 115816
• Main Authors: Gao, Yuhong, Su, Shujing, Zong, Yikai, Zhang, Lili, Guo, Xufei
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.02.2025
• Subjects: Attitude control; Desired model compensation; Fuzzy rules; Gain scheduling; Quadrotors; Robust integral of the sign of the error; Robust integral of the sign of the error; Fuzzy rules; Attitude control; Gain scheduling; Desired model compensation; Quadrotors
• ISSN: 0307-904X
• DOI: 10.1016/j.apm.2024.115816

•A velocity-free adaptive control scheme is proposed with desired model compensation.•A fuzzy logic system is designed to eliminate the chattering of the control system.•The performance of the proposed control scheme is verified on a quadrotor prototype. To solve the instability problem in quadrotor control system subject to parametric uncertainties and external disturbances, an attitude control approach integrated with adaptive fuzzy gain-scheduling desired model compensation robust integral of the sign of the error is proposed. Firstly, the original cascade model of attitude motion is transformed into a strict feedback form with lumped disturbances. Secondly, a desired model compensation robust integral of the sign of the error controller is designed to regulate attitude motion for its invariant properties to lumped disturbances, replacing the velocity state in model-based feedforward control with expected value to ensure the robustness of the system against uncertainties without velocity information. To mitigate the chattering caused by continuous switching control, the fuzzy logic system is used to construct the proposed robust control algorithm, in which robust integral feedback gains associated with the sign function based on fuzzy rules are adaptive scheduled, with the filter tracking error and its derivative as inputs to the fuzzy logic system and robust integral feedback gains as outputs. The stability of the designed closed-loop system is verified by analyzing the convergence of output errors. Finally, the effectiveness and robustness of the proposed method in dealing with the stability of the control system are fully demonstrated by extensive simulations and platform experiments.