Title :
Design and simulation of a self-repairing flight control system for UAV
Author :
Zhengxiang, Qian ; Liang, Tang ; Bin, Zhang ; Xiaozhong, Wang
Author_Institution :
New star Res. Inst. of Appl. Tech., Hefei, China
Abstract :
A self-repairing flight control system based on neural network direct inverse control is proposed to reconfigure the control law in order to restore the control of the damaged UAV. Considering the nonlinear and coupling property of the damaged UAV system, the architecture of neural network is chosen to establish the inverse system of the damaged system for linearization and decoupling. Then PID feedback control is introduced to improve the performance of the inverse system. Theoretical analysis and simulation results show that this control system can be used to restore the control of the damaged UAV when the traditional control fails.
Keywords :
autonomous aerial vehicles; control system synthesis; fault tolerance; feedback; linearisation techniques; neural net architecture; neurocontrollers; nonlinear control systems; three-term control; PID feedback control; control law reconfiguration; coupling property; damaged UAV system; decoupling; linearization; neural network architecture; neural network direct inverse control; nonlinear property; performance improvement; self-repairing flight control system design; self-repairing flight control system simulation; Aerospace control; Artificial neural networks; Biological neural networks; Computer architecture; Control systems; Training; UAV; direct inverse control; neural network; self-repairing;
Conference_Titel :
Control and Decision Conference (CCDC), 2012 24th Chinese
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4577-2073-4
DOI :
10.1109/CCDC.2012.6244278
