Title :
Neural network based adaptive dynamic inversion flight control system design
Author :
Lili ; Hua-min, Zhang
Author_Institution :
Dept. of Aerial Instrum. & Electr. Eng., First Aeronaut. Inst. of Air Force, Xin Yang, China
Abstract :
This paper introduces a neutral network(NN) based adaptive dynamic inversion flight control system. Super-maneuverable flight control law adapts nonlinear inversion design; on-line learning neural networks are implemented to compensate inversion errors due to modeling error or actuator faults. Simulation results show that through adaptively compensating inversion error by neutral networks, the limitation of needing accurate mathematical model in dynamic inversion method is released and the robustness of the whole system is greatly enhanced.
Keywords :
adaptive control; aerospace control; control engineering computing; control system synthesis; neurocontrollers; nonlinear control systems; robust control; adaptive dynamic inversion flight control system; nonlinear inversion design; online learning neural networks; robustness; super-maneuverable flight control law; Adaptive systems; Aerodynamics; Aerospace control; Atmospheric modeling; Biological neural networks; Mathematical model; Nonlinear dynamical systems; adaptive control; dynamic inversion; flight control; neural network;
Conference_Titel :
Intelligent Control and Information Processing (ICICIP), 2011 2nd International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4577-0813-8
DOI :
10.1109/ICICIP.2011.6008215