Time-varying gain extended state observer-based adaptive optimal control for disturbed unmanned helicopter

被引:2
|
作者
Yan, Kun [1 ]
Chen, Hongtian [2 ]
Chen, Chaobo [1 ]
Gao, Song [1 ]
Sun, Jingliang [3 ]
机构
[1] Xian Technol Univ, Coll Elect Informat Engn, Xian 710021, Peoples R China
[2] Shanghai Jiao Tong Univ, Dept Automat, Shanghai 200240, Peoples R China
[3] Beijing Inst Technol, Sch Aerosp Engn, Beijing 100081, Peoples R China
基金
中国国家自然科学基金;
关键词
Unmanned helicopter; Time-varying gain extended state observer; Optimal tracking control; Adaptive dynamic programming; Neural network; MULTIAGENT SYSTEMS; UNKNOWN DYNAMICS; TRACKING CONTROL; QUADROTOR UAV; FEEDBACK;
D O I
10.1016/j.isatra.2024.02.028
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, the robust adaptive optimal tracking control problem is addressed for the disturbed unmanned helicopter based on the time -varying gain extended state observer (TVGESO) and adaptive dynamic programming (ADP) methods. Firstly, a novel TVGESO is developed to tackle the unknown disturbance, which can overcome the drawback of initial peaking phenomenon in the traditional linear ESO method. Meanwhile, compared with the nonlinear ESO, the proposed TVGESO possesses easier and rigorous stability analysis process. Subsequently, the optimal tracking control issue for the original unmanned helicopter system is transformed into an optimization stabilization problem. By means of the ADP and neural network techniques, the feedforward controller and optimal feedback controller are skillfully designed. Compared with the conventional backstepping approach, the designed anti -disturbance optimal controller can make the unmanned helicopter accomplish the tracking task with less energy. Finally, simulation comparisons demonstrate the validity of the developed control scheme.
引用
收藏
页码:1 / 11
页数:11
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