Adaptive Model Predictive Control for Set-Point Tracking of a Single-DOF Flapping-Wing Unmanned Aerial Vehicle

被引：0
|
作者：
Zhu, Bing [1 ]
Zuo, Zongyu [1 ]
机构：
[1] Beihang Univ, Res Div 7, Beijing 100191, Peoples R China
来源：
2017 13TH IEEE INTERNATIONAL CONFERENCE ON CONTROL & AUTOMATION (ICCA) | 2017年
基金：
美国国家科学基金会;
关键词：
Model predictive control; adaptive control; unmanned aerial vehicles; flapping-wing; BIOMIMETIC ROBOTIC INSECTS; LINEAR-SYSTEMS; AIR VEHICLES; STABILITY; FLIGHT; STABILIZATION;
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：
An adaptive model predictive control (MPC) is proposed in this paper to stabilize linear constrained systems with parametric uncertainties. The proposed control is designed by combining linear MPC and an adaptive updating law for uncertain parameters. It is proved that, by using the proposed adaptive MPC, states of the linear system can be stabilized, and the estimated parameters are bounded. The adaptive MPC can be applied to set-point tracking of a single-DOF flapping-wing unmanned aerial vehicle (UAV), where there exist parametric uncertainties and control constraints. Performances of the closed-loop system are illustrated by a simulation example.
引用
收藏
页码：861 / 866
页数：6
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