NDLI: Nonlinear optimized adaptive trajectory control of helicopter

Content Provider	Springer Nature Link
Author	Abaspour, Alireza Sadati, Seyed Hossein Sadeghi, Mohammad
Copyright Year	2015
Abstract	This paper attempts to develop an optimized adaptive trajectory control system for helicopters based on the dynamic inversion method. This control algorithm is implemented by three time-scale separation architectures. Pseudo control hedging (PCH) is used to protect the adaptive element from actuator saturation nonlinearities and also from the inner-outer-loop interaction. In addition, to augment the attitude control system, two online adaptive architectures that employ a neural network are used. By tuning the neural network based on the system model, a better and faster learning will be achieved, but this is a frustrating and time consuming process. Due to complexity in accurate tuning of neural network, this paper introduces a non-dominated sorting genetic algorithm II (NSGA-II) for off-line optimization of the neural network. Thus, in the proposed method, the neural network can compensate model inversion error caused by the deficiency of full knowledge of helicopter dynamics more accurately. The effectiveness of proposed method is demonstrated by numerical simulations.
Starting Page	297
Ending Page	310
Page Count	14
File Format	PDF
ISSN	20956983
Journal	Journal of Control Theory and Applications
Volume Number	13
Issue Number	4
e-ISSN	21980942
Language	English
Publisher	South China University of Technology and Academy of Mathematics and Systems Science, CAS
Publisher Date	2015-11-25
Publisher Place	Guangzhou
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Helicopter nonlinear model dynamic inversion PCH neural network optimization NSGA-II Control Systems Theory, Control Optimization Computational Intelligence Complexity Control, Robotics, Mechatronics
Content Type	Text
Resource Type	Article
Subject	Control and Optimization Control and Systems Engineering Aerospace Engineering

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