Adaptive extremum seeking controller via nonlinear variable gain for uncertainty model multirotor

被引：0
作者：
Zhang, Yanhui [1 ]
Yang, Hua [1 ]
Chen, Yong [2 ]
Chen, Weifang [1 ]
机构：
[1] Zhejiang Univ, Sch Aeronaut & Astronaut, Hangzhou 310027, Peoples R China
[2] Zhejiang Univ, Coll Control Sci & Engn, Hangzhou 310027, Peoples R China
来源：
2022 41ST CHINESE CONTROL CONFERENCE (CCC) | 2022年
基金：
中国博士后科学基金; 中国国家自然科学基金;
关键词：
adaptive extremum seeking controller (AESC); nonlinear variable gain controller; uncertainty model multirotor; QUADROTOR; FEEDBACK;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, we propose an adaptive extremum search control (AESC) scheme for nonlinear underactuated multirotors in order to solve the cross-platform problem of adjusting the wheelbase and loads of multirotors. In AESC, an adaptive learning controller parameter reconstruction method is used, the adaptive extremum seeking cost function is employed to find optimal control parameters, and nonlinear variable gains (NLVG) are used to replace fixed gain in order to achieve real-time adaptive attitude and position tracking control. Experimental and numerical results with quadcopter were demonstrate the proposed AESC has superior tracking accuracy and robustness compared to the traditional cascaded PID control law. The simulation video are avaliable in Video-link: https://youtu.be/TRzlPReNUgY.
引用
收藏
页码：2308 / 2314
页数：7
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