A novel self-tuning fractional order PID control based on optimal model reference adaptive system

Shamseldin, Mohamed Α.; Sallam, Mohamed; Bassiuny, A. M.; Ghany, Α. M. Abdel

doi:10.11591/ijpeds.v10.i1.pp230-241

Cited by 16 publications

(15 citation statements)

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“…The following condition must be hold to achieve the desired performance

italicTs + {GG}_{P} + {GG}_{I} \times \frac{1}{s^{λ}} + {GG}_{D} s^{μ} + 1 = T_{m} s + 1

\frac{\partial e_{m}}{\partial G_{P}} = ([], \frac{G^{2} e}{T_{m} s + 1})

…”

Section: Proposed Methodologymentioning

confidence: 99%

“…At that point, as far as the output tracking error vectors the presented NMSS‐fractional‐order PFC (NMSS‐FOPFC) was planned by means of fractional order cost function. In light of optimal model reference adaptive control (MRAC) a novel self‐tuning fractional order PID (FOPID) control was built up by M. A. Shamseldin et al To accomplish the optimal performance, MRAC parameters have been gotten utilizing the harmony search (HS) optimization technique. Now and again, at the same minute the tuning of the five parameters of FOPID control online expends more calculation time and all the more processing.…”

Section: Recent Research Work: a Brief Reviewmentioning

confidence: 99%

See 1 more Smart Citation

New opposition cuttlefish optimizer based two‐step approach for optimal design of fractional order proportional integral derivative controller for time delay systems

Sumathi¹,

Umasankar²

2019

Int J Numerical Modelling

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In this article, an optimal design of the fractional order proportional integral derivative (FOPID) controller for time delay system is proposed. The proposed optimal design is the combined performance of both the cuttlefish optimizer (CFO) and Opposition-based learning (OBL) scheme called CFOBL scheme. The proposed CFOBL uses the concept of opposition based population initialization and opposition based position updating to improve its searching behavior, computational speed and convergence profile in the basic CFO. In FOPID controller, apart from the three tuning parameters (G P , G I , and G D ) there are two additional tuning parameters that are λ and μ. Here, CFOBL is used to tune the three controller parameters and also to find the optimal values of λ and μ. The uniqueness of the proposed technique is to reduce the FOPID controller's fault in the higher order time delay scheme by the aid of the controller's increase limits. The objective of the proposed technique is chosen by considering the set point parameters and the accomplished parameters from the time delay system. The proposed technique is used to avoid high-order delays and reliability constraints such as small overruns, time resolution and fixed condition defects. This technique is performed on the MATLAB/ Simulink platform and the results are compared with different existing techniques such as Ziegler-Nichols (ZN) tuning method, curve fitting (CF) technique, Wang technique, and regression technique. K E Y W O R D Scuttlefish optimizer, FOPID controller, opposition based two-step approaches, reliability constraints, time delay system

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“…The following condition must be hold to achieve the desired performance

italicTs + {GG}_{P} + {GG}_{I} \times \frac{1}{s^{λ}} + {GG}_{D} s^{μ} + 1 = T_{m} s + 1

\frac{\partial e_{m}}{\partial G_{P}} = ([], \frac{G^{2} e}{T_{m} s + 1})

…”

Section: Proposed Methodologymentioning

confidence: 99%

Section: Recent Research Work: a Brief Reviewmentioning

confidence: 99%

New opposition cuttlefish optimizer based two‐step approach for optimal design of fractional order proportional integral derivative controller for time delay systems

Sumathi¹,

Umasankar²

2019

Int J Numerical Modelling

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show abstract

“…The paper aims to provide a solution to the difficult access that economic conditions have for these automation technologies, developing an own speed control system for any DC motor that requires it, economically viable and applicable to any type of machine, of easy use and implementation in all types of industrial processes [19][20][21][22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

Design and implementation speed control system of DC Motor based on PID control and matlab simulink

Hammoodi

Flayyih

Hamad

2020

IJPEDS

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<span>In this paper, we first write a description of the operation of DC motors taking into account which parameters the speed depends on thereof. The PID (Proportional-Integral-Derivative) controllers are then briefly described, and then applied to the motor speed control already described , that is, as an electronic controller (PID), which is often referred to as a DC motor. The closed loop speed control of a Brush DC motor is developed applying the well-known PID control algorithm. The objective of this work is to designed and simulate a new control system to keep the speed of the DC motor constant before variations of the load (disturbances), automatically depending to the PID controller. The system was designed and implementation by using MATLAB/SIMULINK and DC motor.</span>

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“…DC motor is widely being used in industry due to its low cost, facileness to control, good braking. and good speed regulation performance [1][2][3][4].…”

Section: Introductionmentioning

confidence: 99%

Objective functions modification of GA optimized PID controller for brushed DC motor

Zahir

Alhady

Wahab

et al. 2020

IJECE

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PID Optimization by Genetic Algorithm or any intelligent optimization method is widely being used recently. The main issue is to select a suitable objective function based on error criteria. Original error criteria that is widely being used such as ITAE, ISE, ITSE and IAE is insufficient in enhancing some of the performance parameter. Parameter such as settling time, rise time, percentage of overshoot, and steady state error is included in the objective function. Weightage is added into these parameters based on users’ performance requirement. Based on the results, modified error criteria show improvement in all performance parameter after being modified. All of the error criteria produce 0% overshoot, 29.51%-39.44% shorter rise time, 21.11%-42.98% better settling time, 10% to 53.76% reduction in steady state error. The performance of modified objective function in minimizing the error signal is reduced. It can be concluded that modification of objective function by adding performance parameter into consideration could improve the performance of rise time, settling time, overshoot percentage, and steady state error

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A novel self-tuning fractional order PID control based on optimal model reference adaptive system

Cited by 16 publications

References 0 publications

New opposition cuttlefish optimizer based two‐step approach for optimal design of fractional order proportional integral derivative controller for time delay systems

New opposition cuttlefish optimizer based two‐step approach for optimal design of fractional order proportional integral derivative controller for time delay systems

Design and implementation speed control system of DC Motor based on PID control and matlab simulink

Objective functions modification of GA optimized PID controller for brushed DC motor

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