Modulating function-based system identification for a fractional-order system with a time delay involving measurement noise using least-squares method
DOI10.1080/00207721.2016.1265159zbMath1362.93035OpenAlexW2567179918MaRDI QIDQ5347363
Publication date: 23 May 2017
Published in: International Journal of Systems Science (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00207721.2016.1265159
system identificationtime-delaymeasurement noiseleast squares estimationfractional-order systemsmodulating function
System identification (93B30) Least squares and related methods for stochastic control systems (93E24) Identification in stochastic control theory (93E12) Fractional ordinary differential equations (34A08)
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Cites Work
- Unnamed Item
- Sampled-data \(H_\infty\) synchronization of chaotic Lur'e systems with time delay
- Identification of constitutive parameters for fractional viscoelasticity
- Hybrid control on bifurcation for a delayed fractional gene regulatory network
- Fractional modelling and identification of thermal systems
- Novel techniques in parameter estimation for fractional dynamical models arising from biological systems
- On the closed-loop system identification with fractional models
- Fractional-order system identification based on continuous order-distributions
- A recursive scheme for frequency estimation using the modulating functions method
- Parameter estimation for continuous-time models - a survey
- Synthesis of fractional Laguerre basis for system approximation
- Delay-induced bifurcation in a tri-neuron fractional neural network
- Dα‐Type Iterative Learning Control for Fractional‐Order Linear Time‐Delay Systems
- Identification with block pulse functions, modulating functions and differential operators
- Identification of Parameters of a Half-Order System
- Fractional variational calculus in terms of Riesz fractional derivatives
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