Title :
System identification and analysis of the frequency characteristic of the airborne stabilizing platform
Author :
Yan Dong ; Tao Zhang ; Qing-jun Li ; Wen-ming Li ; Xi-hui Chen
Author_Institution :
Changchun Inst. of Opt. Fine Machinery & Phys., Chinese Acad. of Sci., Changchun, China
Abstract :
In order to resolve the identification problem of the airborne Opto-Electronic stabilizing platform servo system, the detailed discussion and research are made. An identification method based on the ADALINE self-adapting neurons is presented as far as the time domain is concerned and the detailed discussion of the structural design, training design and generalization capability of the neural network is made. A method of obtaining the opened-loop frequency characteristics of the system according to the closed-loop frequency characteristic measuring data as far as the frequency domain is concerned, which resolves the difficulty of some servo systems in directly measuring the opened-loop frequency characteristics.The experimental results prove that the methods used in the paper can still effectively identify the model of the system in the big noises, with the high practical engineering values.
Keywords :
aerospace computing; design engineering; identification; neural nets; servomechanisms; ADALINE self adapting neuron; airborne opto electonic stabilization; frequency characteristic analysis; neural network; opened loop frequency characteristic; servo system; structural design; system identification; training design; Artificial neural networks; Frequency domain analysis; Frequency measurement; Network topology; Neural networks; Neurons; Noise measurement; Servomechanisms; System identification; Transfer functions; frequency characteristics; neural network; system identification;
Conference_Titel :
Computer Engineering and Technology (ICCET), 2010 2nd International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-6347-3
DOI :
10.1109/ICCET.2010.5485500
