Joint estimation of the fractional differentiation orders and the unknown input for linear fractional non-commensurate system
KAUST DepartmentComputational Bioscience Research Center (CBRC)
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Electrical Engineering Program
Permanent link to this recordhttp://hdl.handle.net/10754/621320
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AbstractThis paper deals with the joint estimation of the unknown input and the fractional differentiation orders of a linear fractional order system. A two-stage algorithm combining the modulating functions with a first-order Newton method is applied to solve this estimation problem. First, the modulating functions approach is used to estimate the unknown input for a given fractional differentiation orders. Then, the method is combined with a first-order Newton technique to identify the fractional orders jointly with the input. To show the efficiency of the proposed method, numerical examples illustrating the estimation of the neural activity, considered as input of a fractional model of the neurovascular coupling, along with the fractional differentiation orders are presented in both noise-free and noisy cases.
CitationBelkhatir Z, Laleg-Kirati T-M (2015) Joint estimation of the fractional differentiation orders and the unknown input for linear fractional non-commensurate system. 2015 IEEE Conference on Control Applications (CCA). Available: http://dx.doi.org/10.1109/CCA.2015.7320660.
Conference/Event nameIEEE Conference on Control and Applications, CCA 2015