Robust adaptive fractional-order observer for a class of fractional-order nonlinear systems with unknown parameters

Chen, Kai; Tang, Rongnian; Li, Chuang; Wei, Pengna

doi:10.1007/s11071-018-4368-x

Cited by 22 publications

(10 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…29 Conversely, the Caputo definition is very useful for engineering applications. 30 Compared with the other two definitions, the Grünwald-Letnikov definition is usually applied in the numerical evaluation area. It brings a vital convenience for achieving the numerical solution to the fractional differential equations.…”

Section: Methodsmentioning

confidence: 99%

Fractional order modeling and recognition of nitrogen content level of rubber tree foliage

Tang

et al. 2020

Journal of Near Infrared Spectroscopy

Self Cite

View full text Add to dashboard Cite

The Nondestructive estimation method of nitrogen content level of rubber tree foliage was investigated utilizing nearinfrared (NIR) spectroscopy and Grünwald-Letnikov fractional calculus. Four models, including partial least squares discriminant analysis (PLS-DA), support vector machine (SVM), extreme learning machine (ELM) and convolutional neural networks (CNN) are applied to construct the nitrogen estimation model. The results show that models established by 0.6-order or 1.6-order spectra achieved better performance than models with integer-order spectra. Afterward, the successive projections algorithm (SPA) is applied to reduce the number of variables, which is critical for developing portable nitrogen-level detector devices for rubber trees. The PLS-DA method achieved the best performance with an optimal recognition rate (97.73%) using the 1.6-order spectra. The results suggest that nitrogen content of rubber trees could be reliably estimated by fractional calculus processed NIR spectra. The method proposed here has a wide range of applicability and can provide more useful information for NIR spectral analysis in agriculture as well as other fields.

show abstract

Section: Methodsmentioning

confidence: 99%

Fractional order modeling and recognition of nitrogen content level of rubber tree foliage

Tang

et al. 2020

Journal of Near Infrared Spectroscopy

Self Cite

View full text Add to dashboard Cite

show abstract

“…In addition, several useful results have been acquired for the stability analysis and control of fractional order systems (FOSs). [13][14][15][16][17][18][19][20][21][22][23] In Reference 13, an adaptive fuzzy control is designed for a class of fractional-order neural networks possessing input nonlinearities and dead-zones. A fractional adaptive fuzzy controller is developed for uncertain fractional nonlinear systems with external disturbances in Reference 20, which can guarantee the prescribed performance.…”

Section: Introductionmentioning

confidence: 99%

Event‐triggered adaptive backstepping tracking control for a class of nonlinear fractional order systems

KangShijia

WangHuanqing

ChenMing

et al. 2020

Adaptive Control & Signal

View full text Add to dashboard Cite

This article investigates the problem of event-trigger based adaptive backstepping control for a class of nonlinear fractional order systems. By introducing an appropriate transformation of frequency distributed model, the fractional-order indirect Lyapunov method with 0 < < 1 is obtained. In addition, the event-triggered adaptive controller is developed by employing the event-triggered control approach. Meanwhile, by the proposed adaptive control scheme, all the closed-loop signals are globally uniformly bounded, and the tracking error converges to a small neighborhood of the origin. Finally, simulation results are provided to testify the availability of the presented controller.

show abstract

“…Due to the great efforts devoted by researchers, a large number of valuable results have been reported on fractional calculus. For the details of the most recent advances, one can refer to some excellent papers [9][10][11] and the references therein. The work described in this paper was fully supported by the National Natural Science Foundation of China (61601431, 61573332), the Anhui Provincial Natural Science Foundation (1708085QF141) and the fund of China Scholarship Council (201806345002).…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modelling and simulation of nabla fractional dynamic systems with nonzero initial conditions

Wei

Wang

Tse

et al. 2019

Asian Journal of Control

View full text Add to dashboard Cite

The paper focuses on the numerical approximation of nabla fractional order systems with the conditions of nonzero initial instant and nonzero initial state. First, the inverse nabla Laplace transform is developed and the equivalent infinite dimensional frequency distributed models of discrete fractional order system are introduced. Then, resorting the nabla Laplace transform, the rationality of the finite dimensional frequency distributed model approaching the infinite one is illuminated. Based on this, an original algorithm to estimate the parameters of the approximate model is proposed with the help of vector fitting method. Additionally, the applicable object is extended from a sum operator to a general system. Three numerical examples are performed to illustrate the applicability and flexibility of the introduced methodology.

show abstract

Robust adaptive fractional-order observer for a class of fractional-order nonlinear systems with unknown parameters

Cited by 22 publications

References 33 publications

Fractional order modeling and recognition of nitrogen content level of rubber tree foliage

Fractional order modeling and recognition of nitrogen content level of rubber tree foliage

Event‐triggered adaptive backstepping tracking control for a class of nonlinear fractional order systems

Modelling and simulation of nabla fractional dynamic systems with nonzero initial conditions

Contact Info

Product

Resources

About