Design and real-time implementation of a wireless autopilot using multivariable predictive generalized minimum variance control in the state-space

被引：10

作者：

Silveira, Antonio ^{[1
]}

Silva, Anderson ^{[2
]}

Coelho, Antonio ^{[3
]}

Real, Jose ^{[1
]}

Silva, Orlando ^{[1
]}

机构：

[1] Fed Univ Para, Lab Control & Syst, BR-66075110 Belem, Para, Brazil

[2] Fed Inst Educ Sci & Technol Para, BR-68515000 Parauapebas, Brazil

[3] Univ Fed Santa Catarina, Dept Automat & Syst, BR-88040900 Florianopolis, SC, Brazil

来源：

AEROSPACE SCIENCE AND TECHNOLOGY | 2020年 / 105卷 / 105期

关键词：

Unmanned aerial vehicle; Autopilot; Minimum variance control; Kalman filter; Predictive control; ATTITUDE-CONTROL; QUADROTOR; TRACKING; FLIGHT; MODEL; GUIDANCE; SYSTEM; UAV;

D O I：

10.1016/j.ast.2020.106053

中图分类号：

V [航空、航天];

学科分类号：

08 ; 0825 ;

摘要：

The contribution of this work is the numerical simulation and the experimental assessment of a network distributed control system using an unmanned aerial vehicle and a remote master controller connected by a wireless network. A novel multi-input multi-output long-range predictive horizon minimum variance control approach is developed and implemented in altitude, heading, lateral and longitudinal velocities control problems under the influence of process noise, measurement noise and time-delay. The proposed autopilots exhibited damped and fast response speeds with optimal control and output variance minimization, outperforming a classic model predictive control approach in convincing experimental field tests in real-world environments and scenarios. (C) 2020 Elsevier Masson SAS. All rights reserved.

引用

页数：18

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