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http://dx.doi.org/10.5302/J.ICROS.2008.14.12.1218

Adaptive Control Design for Missile using Neural Networks Augmentation of Existing Controller  

Choi, Kwang-Chan (경상대학교 항공우주공학과)
Sung, Jae-Min (경상대학교 항공우주공학과)
Kim, Byoung-Soo (경상대학교 항공우주공학과)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.14, no.12, 2008 , pp. 1218-1225 More about this Journal
Abstract
This paper presents the design of a neural network based adaptive control for missile is presented. The application model is Exocet MM40, which is derived from missile DATCOM database. Acceleration of missile by tail Fin control cannot be controllable by DMI (Dynamic Model Inversion) directly because it is non-minimum phase system. So, the inner loop consists of DMI and NN (Neural Network) and the outer loop consists of PI controller. In order to satisfy the performances only with PI controller, it is necessary to do some additional process such as gain tuning and scheduling. In this paper, all flight area would be covered by just one PI gains without tuning and scheduling by applying mixture control technique of conventional controller and NN to the outer loop. Also, the simulation model is designed by considering non-minimum phase system and compared the performances to distinguish the validity of control law with conventional PI controller.
Keywords
existing controller; neural network; non-minimum phase;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
Times Cited By SCOPUS : 0
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