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Copyright of Journal on Communication / Tongxin Xuebao is the property of Journal on Communications Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Telecommunication Engineering is the property of Telecommunication Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Virtual reference feedback tuning control is a data-driven control strategy. No model identification of the plant is needed in this control method. Now virtual reference feedback tuning control is a widely used procedure for controller tuning process. Because the asymptotic covariance matrix expression is an important factor in the whole system identification theory. This paper derived the error about the unknown parameter estimation through Taylor series expression. Then it established the corresponding covariance matrix of the parameter estimation error. It obtained the two diagonal sub-matrices in the covariance matrix using some matrix operations. These two diagonal sub-matrices were the asymptotic covariance matrix expression of the two unknown parameter estimation vectors in the closed-loop system. Based on this asymptotic covariance matrix, it obtained an optimal filter by solving an optimization problem which included some trace operation. Finally, the efficiency and possibility of the proposed strategy can be confirmed by the simulation example results. [ABSTRACT FROM AUTHOR]

The linear part's asymptotic covariance matrix expressions of the Wiener system excited by white and colored noise were derived. The asymptotic analysis for noise model, which is excited by colored noise, was added. It is found that, when the model order is replaced by some reproducing kernel function constructed by a group of orthonormal basis functions, above derived two asymptotic covariance matrix expressions could be appropriate to their true sample values, respectively. Thus, the optimization could be considered as the function of input power density. By solving this optimization problem with some constrained conditions, the optimal input signal spectrum for Wiener system could be obtained. Finally, the example simulation confirms the efficiency of proposed strategy. [ABSTRACT FROM AUTHOR]