Journal ArticleDOI
Fractional-order Kalman filters for continuous-time linear and nonlinear fractional-order systems using Tustin generating function
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TLDR
Based on the first-order Taylor expansion formula, the extended fractional-order Kalman filter using Tustin generating function is proposed to improve the accuracy of state estimation.Abstract:
This paper presents the fractional-order Kalman filters using Tustin generating function for linear and nonlinear fractional-order systems involving process noise and measurement noise. By using th...read more
Citations
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Journal ArticleDOI
A Review of Recent Advances in Fractional-Order Sensing and Filtering Techniques.
TL;DR: A comprehensive review of the latest advances in fractional-order sensors and filters, with a focus on design methodologies and their real-life applicability reported in the last decade, can be found in this paper.
Journal ArticleDOI
Tobit Kalman filtering for fractional-order systems with stochastic nonlinearities under Round-Robin protocol
TL;DR: For example, National Natural Science Foundation of China as discussed by the authors gave 61671109, 61803074, 61903065, U1830133 and U1830207, U2030205.
Journal ArticleDOI
Extended Kalman Filters for Continuous-time Nonlinear Fractional-order Systems Involving Correlated and Uncorrelated Process and Measurement Noises
TL;DR: In this paper, the authors investigated fractional-order extended Kalman filters for continuous-time nonlinear fractional order systems using the method of fractionalorder average derivative, which improved the estimation accuracy of the state information and save the computing time.
Posted Content
Robust Stabilization of Fractional-order Interval Systems via Dynamic Output Feedback: An LMI Approach
Pouya Badri,Mahdi Sojoodi +1 more
TL;DR: In this article, a robust dynamic output feedback controller that asymptotically stabilizes interval fractional-order linear time-invariant (FO-LTI) systems is proposed.
Journal ArticleDOI
State Estimation of Continuous-Time Linear Fractional-Order Systems Disturbed by Correlated Colored Noises via Tustin Generating Function
TL;DR: A more accurate state estimation can be achieved using the discretization method via Tustin generation function for the investigated fractional-order systems, compared with Grünwald-Letnikov difference.
References
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Journal ArticleDOI
Discretization schemes for fractional-order differentiators and integrators
YangQuan Chen,Kevin L. Moore +1 more
TL;DR: Two discretization methods for fractional-order differentiator s/sup r/ where r is a real number via continued fraction expansion (CFE) via the Al-Alaoui operator and a direct recursion of the Tustin operator are presented.
Journal ArticleDOI
Fractional calculus in viscoelasticity: An experimental study
TL;DR: In this article, the authors compared fractional and integer order models to describe the viscoelastic properties of soft biological tissue-like materials under harmonic mechanical loading, and found that fractional order models can represent the more complicated rate dependency of material behavior of biological tissues over a broad spectral range.
Journal ArticleDOI
On Riemann and Caputo fractional differences
TL;DR: This paper defines left and right Caputo fractional sums and differences, study some of their properties and then relate them to Riemann-Liouville ones studied before by Miller K. S. and Ross B. and Atici F.M.
Journal ArticleDOI
Studies on fractional order differentiators and integrators: A survey
TL;DR: Fractional order differentiators and integrators of order 12 and 14 are designed and implemented in real time using TMS320C6713 DSP processor and tested using National instruments education laboratory virtual instrumentation system (NIELVIS).
Journal ArticleDOI
Tuning rules for optimal PID and fractional-order PID controllers
Fabrizio Padula,Antonio Visioli +1 more
TL;DR: In this paper, a set of tuning rules for standard (integer-order) PID and fractional-order PID controllers is presented, based on a first-order plus-dead-time model of the process, in order to minimize the integrated absolute error with a constraint on the maximum sensitivity.