185
Views
9
CrossRef citations to date
0
Altmetric
Original Articles

Bias-compensation-based least-squares estimation with a forgetting factor for output error models with white noise

, &
Pages 1700-1709 | Received 04 Sep 2013, Accepted 12 Jun 2014, Published online: 14 Aug 2014

References

  • Ding, F., Chen, T., & Qiu, L. (2006). Bias compensation based recursive least squares identification algorithm for MISO systems. IEEE Transactions on Circuits and Systems – II: Express Brief, 53(5), 349–353.
  • Ding, F., & Yang, J.B. (1998). Computation of noise-to-signal ratio for input-output system. Journal of Tsinghua University, 38(9), 107–110.
  • Ding, J., Han, H., & Ding, F. (2011). Bias compensation based parameter estimation for dual-rate sampled-data systems. In Proceedings of the International Conference on Information Science and Technology (pp. 909–914). Nanjing.
  • Fang, C.Z., & Xiao, D.Y. (1998). [Process identification]. Beijing: Tsinghua University Press. (In Chinese.)
  • Feng, C.B., & Zheng, W.X. (1991). Robust identification of stochastic linear systems with correlated noise. IEE Proceedings-D: Control Theory and Applications, 138(5), 484–492.
  • Garnier, H., Gilson, M., & Zheng, W.X. (2000). A bias-eliminated least-squares method for continuous-time model identification of closed-loop systems. International Journal of Control, 73(1), 38–48.
  • Ikenoue, M., Kanae, S., Yang, Z.J., & Wada, W. (2008). Bias-compensation based method for errors-in-variables model identification. In Proceedings of the 17th World Congress of The International Federation of Automatic Control (pp. 1360–1365). Seoul.
  • Jia, L.J., Tao, R., Kanae, S., Yang, Z.J., & Wada, K. (2011). A unified framework for bias compensation based methods in correlated noise case. IEEE Transactions on Automatic Control, 56(3), 625–629.
  • Kenji, I., Yoshio, M., & Takao, S. (2010). BCLS method for the estimation of continuous-time models in closed loop environment. In Proceedings of the IEEE International Conference on Control Applications (pp. 1369–1373). Yokohama.
  • Ljung, L. (1998). System identification: Theory for the user (2nd Revised ed.), Upper Saddle River, NJ: Prentice Hall.
  • Sagara, S., & Wada, K. (1977). On-line modified least-squares parameter estimation on linear discrete dynamic systems. International Journal of Control, 25(3), 329–343.
  • Soderstrom, T., Hong, M., & Zheng, W.X. (2005). Convergence properties of bias-eliminating algorithms for errors-in-variables identification. International Journal of Adaptive Control and Signal Processing, 19(9), 703–722.
  • Wu, A.G., Chen, S., & Jia, D.L. (2013). Bias compensation recursive least squares estimate algorithm with forgetting factor for output error model (In Chinese). In Proceedings of the 2013 Chinese Control Conference (pp. 1717–1722). Xi'an.
  • Wu, A.G., Qian, Y.Y., & Wu, W.J. (2014). Bias compensation based recursive least squares estimation with forgetting factors for output error moving average systems. IET Signal Processing, 8(5), 483–494.
  • Zhang, Y. (2011). Unbiased identification of a class of multi-input single-output systems with correlated disturbances using bias compensation methods. Mathematical and Computer Modelling, 53, 1810–1819.
  • Zhang, Y., & Yang, H. (2007). Bias compensation recursive least squares identification for output error systems with fed noise. Acta Automatica Sinica, 33(10), 1053–1060.
  • Zheng, W.X. (1998). On a least-squares-based algorithm for identification of stochastic linear systems. IEEE Transactions on Signal Processing, 46(6), 1631–1638.
  • Zheng, W.X. (1999). Least-squares identification of a class of multivariable systems with correlated disturbances. Journal of the Franklin Institute, 336(8), 1309–1324.
  • Zheng, W.X. (2002). A bias correction method for identification of linear dynamic errors-in-variables models. IEEE Transactions on Automatic Control, 47(7), 1142–1147.
  • Zheng, W.X., & Feng, C.B. (1989). Unbiased parameter estimation of linear systems in the presence of input and output noise. International Journal of Adaptive Control and Signal Processing, 3(3), 231–251.
  • Zheng, W.X., & Feng, C.B. (1992). Identification of a class of dynamic errors-in-variables models. International Journal of Adaptive Control and Signal Processing, 6(5), 431–440.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.