TY - JOUR
T1 - Compound Adaptive Fuzzy Quantized Control for Quadrotor and Its Experimental Verification
AU - Zhang, Xiuyu
AU - Wang, Yue
AU - Zhu, Guoqiang
AU - Chen, Xinkai
AU - Li, Zhi
AU - Wang, Chenliang
AU - Su, Chun Yi
N1 - Funding Information:
Manuscript received November 15, 2019; revised February 26, 2020; accepted April 8, 2020. Date of publication May 14, 2020; date of current version February 17, 2021. This work was supported in part by the National Natural Science Foundation of China under Grant 61673101, Grant 61733006, Grant 61973131, and Grant U1813201, in part by the Science and Technology Project of Jilin Province under Grant 20180201009SF, Grant 20170414011GH, Grant 20180201004SF, and Grant 20180101069JC, and in part by the Japan Society for the Promotion of Science under Grant C-18K04212. This article was recommended by Associate Editor C.-M. Lin. (Corresponding authors: Guoqiang Zhu; Xinkai Chen; Zhi Li.) Xiuyu Zhang, Yue Wang, and Guoqiang Zhu are with the School of Automation Engineering, Northeast Electric Power University, Jilin City 132012, China, and also with the Department of Jilin Province International Research Center of Precision Drive and Intelligent Control, Northeast Electric Power University, Jilin City 132012, China (e-mail: zhangxiuyu80@163.com; wangyue930708@163.com; zhugqcn@gmail.com).
Publisher Copyright:
© 2013 IEEE.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021/3
Y1 - 2021/3
N2 - This article aims to realize a precise position and attitude tracking control for the quadrotor using a proposed fuzzy approximator-based compound adaptive fuzzy quantized control scheme. In the control scheme, a quantized output-feedback control for position tracking and a state-feedback quantized control for attitude trajectory tracking are combined to deal with the underactuated and strong coupling problems of the quadrotor. The main contributions are: 1) the adaptive fuzzy quantized control is realized, then the strong nonlinearities caused by the quantizer are effectively mitigated, which implies that the control precision can be improved when a low communication rate is required in the real-time control system of quadrotor; 2) by applying the adaptive fuzzy dynamic surface control (DSC) technique to the underactuated quadrotor control system, the 'explosion of complexity' problem in the backstepping method is overcome and the L∞ tracking performance is achieved with the proposed initializing technique inspired by Zhang et al. This guarantees that the attitude signals promptly converge to the desired trajectories, then the underactuated problem of the quadrotor is overcome by solving the designed adaptive fuzzy-quantized control equations; and 3) the experiments on the platform of the Quanser Qball-X4 quadrotor are conducted and the effectiveness of the proposed control scheme is validated.
AB - This article aims to realize a precise position and attitude tracking control for the quadrotor using a proposed fuzzy approximator-based compound adaptive fuzzy quantized control scheme. In the control scheme, a quantized output-feedback control for position tracking and a state-feedback quantized control for attitude trajectory tracking are combined to deal with the underactuated and strong coupling problems of the quadrotor. The main contributions are: 1) the adaptive fuzzy quantized control is realized, then the strong nonlinearities caused by the quantizer are effectively mitigated, which implies that the control precision can be improved when a low communication rate is required in the real-time control system of quadrotor; 2) by applying the adaptive fuzzy dynamic surface control (DSC) technique to the underactuated quadrotor control system, the 'explosion of complexity' problem in the backstepping method is overcome and the L∞ tracking performance is achieved with the proposed initializing technique inspired by Zhang et al. This guarantees that the attitude signals promptly converge to the desired trajectories, then the underactuated problem of the quadrotor is overcome by solving the designed adaptive fuzzy-quantized control equations; and 3) the experiments on the platform of the Quanser Qball-X4 quadrotor are conducted and the effectiveness of the proposed control scheme is validated.
KW - Adaptive quantized control
KW - quadrotor
KW - robust adaptive control
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U2 - 10.1109/TCYB.2020.2987811
DO - 10.1109/TCYB.2020.2987811
M3 - Article
C2 - 32413942
AN - SCOPUS:85101123824
SN - 2168-2267
VL - 51
SP - 1121
EP - 1133
JO - IEEE Transactions on Cybernetics
JF - IEEE Transactions on Cybernetics
IS - 3
M1 - 9092979
ER -