INVSID 1.0: An Inverse System Identification Toolbox for MATLAB
Author:
Affiliation:
1. College of Optical, Mechanical and Electrical Engineering, Zhejiang A&F University, Hangzhou 311300, China
2. Institut für Elektrische Informationstechnik, Technische Universität Clausthal, 38678 Clausthal-Zellerfeld, Germany
Abstract
Funder
Natural Science Foundation of Zhejiang province, P.R. China
University Research Development Foundation in Zhejiang A&F University, P.R. China
Publisher
MDPI AG
Link
https://www.mdpi.com/2076-3417/14/15/6838/pdf
Reference28 articles.
1. Goodwin, G.C., Graebe, S.F., and Salgado, M.E. (2001). Control System Design, Prentice Hall.
2. Golub, G.H., and Van Loan, C.F. (2012). Matrix Computations, John Hopkins University Press.
3. Jung, Y. (2018). Inverse System Identification with Applications in Predistortion, Linköping University.
4. On inversion-based approaches for feedforward and ILC;Oomen;Mechatronics,2018
5. Zhou, K., Doyle, J.C., and Glover, K. (1996). Robust and Optimal Control, Prentice Hall.
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