Robust control for an unmanned helicopter with constrained flapping dynamics

被引：12

作者：

Li, Rong ^{[1
]}

Chen, Mou ^{[1
]}

Wu, Qingxian ^{[1
]}

机构：

[1] Nanjing Univ Aeronaut & Astronaut, Coll Automat Engn, Nanjing 210016, Jiangsu, Peoples R China

来源：

CHINESE JOURNAL OF AERONAUTICS | 2018年 / 31卷 / 11期

基金：

中国国家自然科学基金;

关键词：

Altitude control; Attitude control; Barrier Lyapunov function; Control constraint; Prescribed performance; Unmanned helicopter; ADAPTIVE NEURAL-CONTROL; NONLINEAR-SYSTEMS; TRACKING CONTROL; DISTURBANCE OBSERVER; INPUT SATURATION; SURFACE CONTROL; NETWORK CONTROL; ATTITUDE; MPC;

D O I：

10.1016/j.cja.2018.08.007

中图分类号：

V [航空、航天];

学科分类号：

08 ; 0825 ;

摘要：

In this paper, a neural network based adaptive prescribed performance control scheme is proposed for the altitude and attitude tracking system of the unmanned helicopter in the presence of state and output constraints. For handling the state constraints, the barrier Lyapunov function and the saturation function are employed. And, the prescribed performance method is used to deal with the flapping angle constraints for the unmanned helicopter. It is proved that the proposed control approach can ensure that all the signals of the resulting closed-loop system are bounded, and the tracking errors are within the prescribed performance bounds for all time. The numerical simulation is given to illustrate the performance of the proposed scheme. (C) 2018 Production and hosting by Elsevier Ltd. on behalf of Chinese Society of Aeronautics and Astronautics.

引用

页码：2136 / 2148

页数：13

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