Details of Research Outputs

TitleOn the input design for kernel-based regularized LTI system identification: Power-constrained inputs
Author (Name in English or Pinyin)
Mu, B.1; Chen, T.2; Ljung, L.1
Date Issued2017-12-12
Conference Name2017 IEEE 56th Annual Conference on Decision and Control (CDC)
Source Publication2017 IEEE 56th Annual Conference on Decision and Control (CDC)
Conference PlaceMelbourne, VIC, Australia
DOI10.1109/CDC.2017.8264437
Funding Project国家自然科学基金项目
Firstlevel Discipline信息科学与系统科学
Education discipline科技类
CN9781509028733
Published range国外学术期刊
Volume Issue Pages5262-5267
References
[1] R. Mehra, "Optimal input signals for parameter estimation in dynamic systems-survey and new results," IEEE Transactions on Automatic Control, vol. 19, no. 6, pp. 753-768, 1974.
[2] T. Soderstrom and P. Stoica, System identification. Prentice Hall International, 1989.
[3] L. Ljung, System identification: Theory for the user. Upper Saddle River, NJ: Prentice-Hall, 1999.
[4] G. C. Goodwin and R. L. Payne, Dynamic system identification: experiment design and data analysis. New York: Academic press, 1977.
[5] M. J. Levin, "Optimum estimation of impulse response in the presence of noise," IRE Transactions on Circuit Theory, vol. 7, no. 1, pp. 50-56, 1960.
[6] V. S. Levadi, "Design of input signals for parameter estimation," IEEE Transactions on Automatic Control, vol. 11, no. 2, pp. 205-211, 1966.
[7] M. Aoki and R. M. Staley, "On input signal synthesis in parameter identification," Automatica, vol. 6, no. 3, pp. 431-440, 1970.
[8] S. Arimoto and H. Kimura, "Optimum input test signals for system identification-an information-theoretical approach," International Journal of Systems Science, vol. 1, no. 3, pp. 279-290, 1971.
[9] M. Gevers, "Identification for control: From the early achievements to the revival of experiment design," European journal of control, vol. 11, no. 4-5, pp. 335-352, 2005.
[10] H. Jansson and H. Hjalmarsson, "Input design via lmis admitting frequency-wise model specifications in confidence regions," IEEE transactions on Automatic Control, vol. 50, no. 10, pp. 1534-1549, 2005.
[11] R. Hildebrand and M. Gevers, "Identification for control: optimal input design with respect to a worst-case v-gap cost function," SIAM Journal on Control and Optimization, vol. 41, no. 5, pp. 1586-1608, 2003.
[12] H. Hjalmarsson, "System identification of complex and structured systems," European journal of control, vol. 15, no. 3-4, pp. 275-310, 2009.
[13] G. Pillonetto and G. De Nicolao, "A new kernel-based approach for linear system identification," Automatica, vol. 46, no. 1, pp. 81-93, 2010.
[14] G. Pillonetto, A. Chiuso, and G. De Nicolao, "Prediction error identification of linear systems: a nonparametric gaussian regression approach," Automatica, vol. 47, no. 2, pp. 291-305, 2011.
[15] T. Chen, H. Ohlsson, and L. Ljung, "On the estimation of transfer functions, regularizations and gaussian processes-revisited," Automatica, vol. 48, no. 8, pp. 1525-1535, 2012.
[16] T. Chen, M. S. Andersen, L. Ljung, A. Chiuso, and G. Pillonetto, "System identification via sparse multiple kernel-based regularization using sequential convex optimization techniques," IEEE Transactions on Automatic Control, vol. 59, no. 11, pp. 2933-2945, 2014.
[17] G. Pillonetto, F. Dinuzzo, T. Chen, G. De Nicolao, and L. Ljung, "Kernel methods in system identification, machine learning and function estimation: A survey," Automatica, vol. 50, no. 3, pp. 657-682, 2014.
[18] G. Pillonetto and A. Chiuso, "Tuning complexity in regularized kernelbased regression and linear system identification: The robustness of the marginal likelihood estimator," Automatica, vol. 58, pp. 106-117, 2015.
[19] B. Mu, T. Chen, and L. Ljung, "Tuning of hyperparameters for fir models-an asymptotic theory," in Proceedings of the 20th IFAC World Congress, Toulouse, France, 2017.
[20] T. Chen and L. Ljung, "On kernel design for regularized lti system identification," arXiv preprint arXiv:1612.03542, 2017.
[21] B. Mu, T. Chen, and L. Ljung, "On asymptotic properties of hyperparameter estimators for kernel-based regularization methods," arXiv preprint arXiv:1707.00407, 2017.
[22] B. Mu and T. Chen, "On input design for regularized lti system identification: Power-constrained input," in arXiv preprint arXiv:1708.05539, 2017.
[23] Y. Fujimoto and T. Sugie, "Informative input design for kernel-based system identification," in Proceedings of IEEE Conference on Decision and Control. IEEE, 2016, pp. 4636-4639.
[24] M. C. Grant and S. P. Boyd, "Cvx: Matlab software for disciplined convex programming, version 2.1," Available from http://cvxr.com/cvx/, 2016.
[25] F. P. Carli, T. Chen, and L. Ljung, "Maximum entropy kernels for system identification," IEEE Transactions on Automatic Control, vol. 62, no. 3, pp. 1471-1477, March 2017.
Citation statistics
Cited Times [WOS]:0   [WOS Record]     [Related Records in WOS]
Document TypeConference paper
Identifierhttps://irepository.cuhk.edu.cn/handle/3EPUXD0A/726
CollectionSchool of Data Science
Affiliation
1.Division of Automatic Control, Department of Electrical Engineering, Linköping University, Linköping, SE-58183, Sweden
2.School of Science and Engineering, Chinese University of Hong Kong, Shenzhen, 518172, China
Recommended Citation
GB/T 7714
Mu, B.,Chen, T.,Ljung, L. On the input design for kernel-based regularized LTI system identification: Power-constrained inputs[C],2017.
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