Research Article | OPEN ACCESS
Optimized Reconfigurable Control Design for Aircraft using Genetic Algorithm
1Arsalan H.Khan, 1Zhang Weiguo, 21Zeashan.H.Khan, 1Shi Jingping
1Northwestern Polytechnical University, Xi'an, China
2Comwave Institute of Science and Technology, Islamabad, Pakistan
Research Journal of Applied Sciences, Engineering and Technology 2013 24:4653-4662
Received: March 07, 2013 | Accepted: April 12, 2013 | Published: December 25, 2013
Abstract
In this study, we propose a Genetic Algorithm (GA) based modular reconfigurable control scheme for an over-actuated non-linear aircraft model. The reconfiguration of the flight controller is achieved for the case of control surface faults/failures using a separate control distribution algorithm without modifying the base-line control law. The baseline Multi-Input Multi-Output (MIMO) Linear Quadratic Regulator (LQR) is optimized using GA to produce desired moment commands. Then, a GA based weighted pseudo-inverse method is used for effective distribution of commands between redundant control surfaces. Control surface effectiveness levels are used to redistribute the control commands to healthy actuators when a fault or failure occurs. Simulation results using ADMIRE aircraft model show the satisfactory performance in accommodating different faults, which confirm the efficiency of optimized reconfigurable design strategy.
Keywords:
Control allocation, genetic algorithm, linear quadratic regulator, non-linear aircraft model, pseudoinverse method,
Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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