Volume 1, Number 1 (2016)
Year Launched: 2016
Journal Menu
Archive
Previous Issues
Why Us
-  Open Access
-  Peer-reviewed
-  Rapid publication
-  Lifetime hosting
-  Free indexing service
-  Free promotion service
-  More citations
-  Search engine friendly
Contact Us
Email:   service@scirea.org
Home > Journals > SCIREA Journal of Electrics, Communication > Archive > Paper Information

Asymptotic statistical analysis of virtual reference feedback tuning control

Volume 1, Issue 1, October 2016    |    PP. 1-14    |PDF (354 K)|    Pub. Date: October 16, 2016
268 Downloads     1964 Views  

Author(s)
Hong Wang-jian, Dipartimento di Elettronica, Informazione Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milano, Italy
Guo Xiao-yong, School of Science, Henan University of Engineering, Zhengzhou 451191, China

Abstract
Virtual reference feedback tuning control is a data-driven control strategy. No model identification of the plant is needed in this method. As the asymptotic covariance matrix is an important factor in the whole system identification theory. So here the error about the unknown parameter estimation is derived through Taylor series expression. Then the corresponding covariance matrix of the parameter estimation error is established. The two diagonal sub-matrices in the covariance matrix are obtained using some matrix operations. These two diagonal sub- matrices are the asymptotic covariance matrix expression of the two unknown parameter estimation vectors in the closed-loop system. Based on this asymptotic covariance matrix, an optimal filter is obtained by solving an optimization problem which includes some trace operation. Finally, the efficiency and possibility of the proposed strategy can be confirmed by the simulation example results.

Keywords
Virtual reference feedback tuning control; Asymptotic analysis; Stochastic optimization

Cite this paper
Hong Wang-jian, Guo Xiao-yong, Asymptotic statistical analysis of virtual reference feedback tuning control, SCIREA Journal of Electrics, Communication. Vol. 1 , No. 1 , 2016 , pp. 1 - 14 .

References

[ 1 ] Guido. Guardabassi. Virtual reference direct method: An off-line approach to data-based control system design[J]. IEEE Transactions of Automatic Control, 2002, 45(5): 954-960.
[ 2 ] M.C.Campi. Virtual reference feedback tuning: a direct method for the design of feedback controllers [J]. Automatica, 2002, 38(4): 1337-1346.
[ 3 ] M.C.Campi. A. Lechini. An application of the Virtual Reference Feedback Tuning method to a Benchmark problem[J]. European Journal of Control, 2003, 9(2):66-76.
[ 4 ] A.Lechini. M.C.Campi. Virtual reference feedback tuning for two degrees of freedom controllers [J]. International Journal of Adaptive Control and Signal Processing, 2002, 16(10): 355-371.
[ 5 ] M.C.Campi. Direct nonlinear control design: the virtual reference feedback tuning approach[J]. IEEE Transactions of Automatic Control, 2006, 51(1): 14-27.
[ 6 ] Alexandre S. Bazanella. Iterative minimization of H2 control performance criteria[J]. Automatica, 2008, 44(3): 2549-2559.
[ 7 ] R hilderbrand. Pre-filtering in iterative feedback tuning: optimization of the pre-filter for accuracy[J]. IEEE Transactions of Automatic Control, 2004, 49(8): 1801-1805.
[ 8 ] Vijay k Shetty. Priority based assignment and routing of unmanned combat aerial vehicles[J]. Computer & Operations Research, 2008, 35(10): 1813-1828.
[ 9 ] Silven S. A neural network based optimization algorithm for multiple targets tracking[J]. IEEE Journal of Oceanic Engineering, 2010, 37(4): 56-62.
[ 10 ] Zhang Wen xiu. Incomplete information system and its optimal selection [J]. Computer and Mathematics with Application, 2004, 48(5): 691-698.
[ 11 ] Wang Guo yin. Rough set extensions in incomplete information systems[J]. Frontiers of Electronical and Electronic Engineering, 2008, 3(4): 399-405.

Submit A Manuscript
Review Manuscripts
Join As An Editorial Member
Most Views
Article
by Sergey M. Afonin
2935 Downloads 42652 Views
Article
by Syed Adil Hussain, Taha Hasan Associate Professor
2295 Downloads 19851 Views
Article
by Omprakash Sikhwal, Yashwant Vyas
2366 Downloads 16583 Views
Article
by Munmun Nath, Bijan Nath, Santanu Roy
2263 Downloads 16508 Views
Upcoming Conferences