Note on fractional-order proportional–integral–differential controller design

Yeroğlu, Celaleddin; Tan, Nusret

doi:10.1049/iet-cta.2010.0746

Cited by 138 publications

(63 citation statements)

References 22 publications

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“…This algorithm will use a following procedure to estimate hessian matrix. 9 Therefore weight setting algorithm will be as bellowing form.…”

Section: Levenberg Marquardt Training Methodsmentioning

confidence: 99%

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Torque Control of AC Motor with FOPID Controller Based on Fuzzy Neural Algorithm

Farahani¹

2017

IJICS

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“…This algorithm will use a following procedure to estimate hessian matrix. 9 Therefore weight setting algorithm will be as bellowing form.…”

Section: Levenberg Marquardt Training Methodsmentioning

confidence: 99%

“…For this reason this controller is one of the most widely controllers between FOPID controllers. In the design of this controller, it has been tried that tracking in addition to noise and distortion cancellation is considered which it shows the high flexibility of this controller [9].…”

Section: Optimal Pid Controllermentioning

confidence: 99%

Torque Control of AC Motor with FOPID Controller Based on Fuzzy Neural Algorithm

Farahani¹

2017

IJICS

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“…Daha sonraki çalışmalarda, P parametrelerinin elde edilmesi için birçok tasarım yöntemi önerilmiştir [16]- [18]. Ayrıca, literatürde FOPID kontrolör parametrelerini ayarlayan birçok nümerik yöntem bulunmaktadır.…”

Section: Introductionunclassified

Two degrees of freedom FOPID control loop design via SMDO algorithm

Ateş¹,

Yeroğlu²

2016

Pamukkale J Eng Sci

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“…Tuning of H∞ controllers for fractional singleinput single-output (SISO) system was suggested in [12]. In [16], tuning method for PI D based on Ziegler-Nichols and Astrom-Hagglund tuning rules is presented.…”

Section: Introductionmentioning

confidence: 99%

Stabilization of Inverted Cart-Pendulum System Using Controller: A Frequency-Domain Approach

Mishra

Chandra

2013

Chinese Journal of Engineering

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This paper focuses on the angular stabilization of inverted cart-pendulum system using PI D controller. The tuning of PI D controller is formulated as a nonlinear optimization problem, in which the objective function is composed of five design conditions in frequency domain. Particle swarm optimization technique has been used for optimizing PI D parameters. Also a PID controller has been designed based on same specifications, and a comparative study has been carried out. All the responses have been calculated using FOMCON toolbox of Matlab/Simulink.

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Note on fractional-order proportional–integral–differential controller design

Cited by 138 publications

References 22 publications

Torque Control of AC Motor with FOPID Controller Based on Fuzzy Neural Algorithm

Torque Control of AC Motor with FOPID Controller Based on Fuzzy Neural Algorithm

Two degrees of freedom FOPID control loop design via SMDO algorithm

Stabilization of Inverted Cart-Pendulum System Using Controller: A Frequency-Domain Approach

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