Prediction Error Identification of Controller Parameters in Virtual Reference Feedback Tuning

doi:10.3969/j.issn.1000-565X.2013.05.003

Journal of South China University of Technology (Natural Science Edition) ›› 2013, Vol. 41 ›› Issue (5): 15-21.doi: 10.3969/j.issn.1000-565X.2013.05.003

• Electronics, Communication & Automation Technology • Previous Articles Next Articles

Prediction Error Identification of Controller Parameters in Virtual Reference Feedback Tuning

Tang Xiao-jun Wang Dao-bo Tang De-zhi Li Meng

College of Automation Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,Jiangsu，China

Received:2012-09-24 Revised:2013-01-03 Online:2013-05-25 Published:2013-04-01
Contact: 唐小军(1978-) ，男，博士生，主要从事飞行控制、自适应控制研究． E-mail:tangxiaojun1978@163.com
About author:唐小军(1978-) ，男，博士生，主要从事飞行控制、自适应控制研究．
Supported by:
航空科学基金资助项目( 20101352015)

Abstract

Abstract:

In this paper,a method that minimizes the 2-norm-type cost function consisted of a set of observed data,namely the virtual reference feedback tuning,is employed to directly design a dual-controller for an unknown system.In this method,the fixed part decomposed from the feedforward controller is combined with the feedback controllerto form a filter,a normal formula of the prediction error identification is derived by re-parameterizing theoriginal input /output relationships,and a separable iterative nonlinear least square method is used to estimate theunknown parameter vectors of the controller.Moreover,the convergence of the proposed algorithm is theoreticallyanalyzed,and the effectiveness of the algorithm is finally verified by simulations.

Key words: virtual reference feedback tuning, prediction error identification, filter, re-parameterization, nonlinearleast square method

CLC Number:

TP273

Tang Xiao-jun Wang Dao-bo Tang De-zhi Li Meng. Prediction Error Identification of Controller Parameters in Virtual Reference Feedback Tuning[J]. Journal of South China University of Technology (Natural Science Edition), 2013, 41(5): 15-21.

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Prediction Error Identification of Controller Parameters in Virtual Reference Feedback Tuning

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