Classical controller design techniques for fractional order case

Yeroğlu, Celaleddin; Tan, Nusret

doi:10.1016/j.isatra.2011.03.004

Cited by 45 publications

(19 citation statements)

References 29 publications

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“…A desired time response specifications of the reference system such as maximum overshoot, peak time, rise time, settling time can be configured by using the appropriate values of the parameters γ and c w of the closed loop transfer function of the reference system [13][14][15][16]. The parameter γ increases the overshoot and c w decreases settling time of step response of BICL.…”

Section: B Teoritical Backgroundmentioning

confidence: 99%

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Tuning of fractional order PID with master-slave stochastic multi-parameter divergence optimization method

Ateş

Alagöz

Yeroğlu

et al. 2014

ICFDA'14 International Conference on Fractional Differentiation and Its Applications 2014

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This paper presents master-slave stochastic multiparameters divergence optimization (SMDO) method for tuning of fractional order proportional-integral-derivative (FOPID) controllers. Bode's ideal control loop (BICL) is used as a reference model that guides the optimization process. Masterslave SMDO performs optimization of FOPID and BICL parameters together. In the first stage called as locking, step responses of FOPID and BICL approximate each other. In the second stage called as drifting, BICL guides tuning of the FOPID towards a desired step response. One of the advantages of presented optimization approach is that both optimization of the reference model (BICL) and controller (FOPID) cooperates and the tuning of FOPID is governed by BICL in the drifting stage. Operation and performance of the proposed algorithm are demonstrated by simulation examples.

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Section: B Teoritical Backgroundmentioning

confidence: 99%

“…Because, properties of BICL step response such as maximum overshoot, peak time, rise time, settling time, can be configurable [15,16].…”

Section: Introductionmentioning

confidence: 99%

Tuning of fractional order PID with master-slave stochastic multi-parameter divergence optimization method

Ateş

Alagöz

Yeroğlu

et al. 2014

ICFDA'14 International Conference on Fractional Differentiation and Its Applications 2014

Self Cite

View full text Add to dashboard Cite

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“…First one is decentralized single input single output system and second method is decoupler design to cancels the interaction effect between two loops. Decentralized controller is preferred in many MIMO dynamic process because of its straight forward approach and simple to design, easy to tune, failure of one loop will not affect whole process [4][5]. It is very difficult to understand the loop interaction of dynamic nonlinear process [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Multi-loop decentralized controller for two interacting conical tank process

Lakshmanaprabu

Banu

2014

2014 International Conference on Control, Instrumentation, Communication and Computational Technologies (ICCICCT)

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In proposed method Multiloop decentralized PI controller with decoupler is designed for highly nonlinear interacting process. Relative Gain Array is computed for the interaction analysis and variable pairing. S ingular value decomposition matrix technique used and condition number is calculated to determine the illness of the plant. Multi loop PI is designed and decoupler controller is implemented to reduce the loop interaction effect. Two input two output processes are decomposed and controlled by two decentralized S IS O controllers and controller performances were shown. S imulation results are given for the proposed method.

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“…The FOBD is a discrete approximation of fractional-order differentiation [13][14][15]. A fractional-order PD (FOPD) controller is a special case of the fractional-order PID controller [16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31] where the above two tuning parameters have the third fractional differentiation order one. This leads to new CLS transient states [13,[32][33][34].…”

Section: Introductionmentioning

confidence: 99%

The variable, fractional-order discrete-time PD controller in the IISv1.3 robot arm control

et al. 2013

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Abstract:In this paper, the discrete differentiation order functions of the variable, fractional-order PD controller (VFOPD) are considered. In the proposed VFOPD controller, a variable, fractional-order backward difference is applied to perform closed-loop, system error, discrete-time differentiation. The controller orders functions which may be related to the controller input or output signal or an input and output signal. An example of the VFOPD controller is applied to the robot arm closed-loop control due to system changes in moment of inertia. The close-loop system step responses are presented. PACS IntroductionPID control strategies, for over 60 years, have been a fundamental structure in the control with feedback field [1, 2]. The PD controller structure is used in electrical drives [3], in robotics [4][5][6] and where the robot arm has integration properties driven by DC motor systems [5].In such a closed-loop system (CLS) structure, a zero steady state is achieved fora stepwise reference input [7][8][9][10][11][12]. Additionally a PD controller improves the CLS sta- *

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Classical controller design techniques for fractional order case

Cited by 45 publications

References 29 publications

Tuning of fractional order PID with master-slave stochastic multi-parameter divergence optimization method

Tuning of fractional order PID with master-slave stochastic multi-parameter divergence optimization method

Multi-loop decentralized controller for two interacting conical tank process

The variable, fractional-order discrete-time PD controller in the IISv1.3 robot arm control

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