Attitude regulation for unmanned quadrotors using adaptive fuzzy gain-scheduling sliding mode control

被引:173
作者
Yang, Yueneng [1 ]
Yan, Ye [1 ]
机构
[1] Natl Univ Def Technol, Coll Aerosp Sci & Engn, Changsha 410073, Hunan, Peoples R China
基金
中国国家自然科学基金;
关键词
Attitude control; Sliding mode control; Fuzzy rules; Gain scheduling; Robustness; Quadrotor; FEEDBACK-LINEARIZATION; TRACKING CONTROLLER; SYSTEM; POSITION; DESIGN; GUIDANCE;
D O I
10.1016/j.ast.2016.04.005
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
This paper addresses the problem of attitude regulation for unmanned quadrotors with parametric uncertainties and external disturbances. A novel adaptive fuzzy gain-scheduling sliding mode control (AFGS-SMC) approach is proposed for attitude regulation of unmanned quadrotors. First, the kinematics model and dynamics model of attitude motion are derived, and the problem of attitude regulation is formulated. Second, a sliding mode controller is designed to regulate the attitude motion for its invariant properties to parametric uncertainties and external disturbances. The global stability and error convergence of the closed-loop system are proven by using the Lyapunov stability theorem. In order to reduce the chattering induced by continual switching control of SMC, the fuzzy logic system (FLS) is employed to design the AFGS-SMC, in which the control gains related to sign function are scheduled adaptively according to fuzzy rules, with sliding surface and its differential as FLS inputs and control gains as FLS outputs. Finally, the effectiveness and robustness of the proposed control approach are demonstrated via simulation results. (C )2016 Elsevier Masson SAS. All rights reserved.
引用
收藏
页码:208 / 217
页数:10
相关论文
共 45 条
[31]  
Ton T. C., 2015, AIAA GUID NAV CONTR
[32]   Fractional order adaptive fuzzy sliding mode controller for a position servo system subjected to aerodynamic loading and nonlinearities [J].
Ullah, Nasim ;
Wang Shaoping ;
Khattak, Muhammad Irfan ;
Shafi, Muhammad .
AEROSPACE SCIENCE AND TECHNOLOGY, 2015, 43 :381-387
[33]  
Wang J., 2011, INFOTECH AEROSPACE
[34]  
Wang S. H., 2013, CONTROL THEORY APPL, V30, P1110
[35]   Data-based output feedback control using least squares estimation method for a class of nonlinear systems [J].
Wang, Zhuo ;
Liu, Derong .
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2014, 24 (18) :3061-3075
[36]  
Yacef F, 2014, INT CONF UNMAN AIRCR, P920, DOI 10.1109/ICUAS.2014.6842341
[37]  
Yilmaz Emre, 2014, AIAA ATM FLIGHT MECH
[38]   Adaptive Fuzzy Control of Strict-Feedback Nonlinear Time-Delay Systems With Unmodeled Dynamics [J].
Yin, Shen ;
Shi, Peng ;
Yang, Hongyan .
IEEE TRANSACTIONS ON CYBERNETICS, 2016, 46 (08) :1926-1938
[39]   Data-Driven Process Monitoring Based on Modified Orthogonal Projections to Latent Structures [J].
Yin, Shen ;
Wang, Guang ;
Gao, Huijun .
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2016, 24 (04) :1480-1487
[40]   Performance Monitoring for Vehicle Suspension System via Fuzzy Positivistic C-Means Clustering Based on Accelerometer Measurements [J].
Yin, Shen ;
Huang, Zenghui .
IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2015, 20 (05) :2613-2620