Novel morphing wing actuator control-based Particle Swarm Optimisation

Author:

Khan S.,Grigorie T. L.,Botez R. M.ORCID,Mamou M.,Mébarki Y.

Abstract

AbstractThe paper presents the design and experimental testing of the control system used in a new morphing wing application with a full-scaled portion of a real wing. The morphing actuation system uses four similar miniature brushless DC (BLDC) motors placed inside the wing, which execute a direct actuation of the flexible upper surface of the wing made from composite materials. The control system of each actuator uses three control loops (current, speed and position) characterised by five control gains. To tune the control gains, the Particle Swarm Optimisation (PSO) method is used. The application of the PSO method supposed the development of a MATLAB/Simulink® software model for the controlled actuator, which worked together with a software sub-routine implementing the PSO algorithm to find the best values for the five control gains that minimise the cost function. Once the best values of the control gains are established, the software model of the controlled actuator is numerically simulated in order to evaluate the quality of the obtained control system. Finally, the designed control system is experimentally validated in bench tests and wind-tunnel tests for all four miniature actuators integrated in the morphing wing experimental model. The wind-tunnel testing treats the system as a whole and includes, besides the evaluation of the controlled actuation system, the testing of the integrated morphing wing experimental model and the evaluation of the aerodynamic benefits brought by the morphing technology on this project. From this last perspective, the airflow on the morphing upper surface of the experimental model is monitored by using various techniques based on pressure data collection with Kulite pressure sensors or on infrared thermography camera visualisations.

Publisher

Cambridge University Press (CUP)

Subject

Aerospace Engineering

Reference49 articles.

1. 37. Khan, S. , Botez, R. M. and Grigorie, T.L. A new method for tuning PI gains for position control of BLDC motor-based wing morphing actuators, AIAA Modeling and Simulation Technologies Conference, 22–26 June 2015, Dallas, TX, US.

2. 38. Kennedy, J. and Eberhart, R. Particle Swarm Optimization, Proceedings of IEEE International Conference on Neural Networks (ICNN), Australia, 1995, pp 1942–1948.

3. Numerical and experimental validation of a full scale servo-actuated morphing aileron model

4. Distributed actuation concepts for a morphing aileron device

5. Design and wind tunnel experimental validation of a controlled new rotary actuation system for a morphing wing application

Cited by 18 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3