Fractional Order PID Controller Design for DC Motor Speed Control System via Flower Pollination Algorithm

Puangdownreong, Deacha

doi:10.37936/ecti-eec.2019171.215368

Cited by 24 publications

(20 citation statements)

References 33 publications

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“…Design techniques, optimization tools and practical implementations of PI λ D µ controllers are discussed in [7][8][9][10][11][12][13][14]. In particular, the FO derivative of the PD µ can lead to performance improvements in the transient behavior with respect to the classical PD in many motion control applications [15][16][17][18][19][20][21][22][23][24].…”

Section: Introductionmentioning

confidence: 99%

Experimental Assessment of Fractional-Order PDD1/2 Control of a Brushless DC Motor with Inertial Load

2020

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The application of Fractional Calculus to control mechatronic devices is a promising research area. The most common approach to Fractional-Order (FO) control design is the PIλDµ scheme, which adopts integrals and derivatives of non-integer order λ and µ. A different possible approach is to add FO terms to the PID control, instead of replacing integer order terms; for example, in the PDD1/2 scheme, the half-derivative term is added to the classical PD. In the present paper, by mainly focusing on the transitory behaviour, a comparison among PD, PDµ, and PDD1/2 control schemes is carried out, with reference to a real-world mechatronic implementation: a position-controlled rotor actuated by a DC brushless motor. While using a general non-dimensional approach, the three control schemes are first compared by continuous-time simulations, and tuning criteria are outlined. Afterwards, the effects of the discrete-time digital implementation of the controllers are investigated by both simulation and experimental tests. The results show how PDD1/2 is an effective and almost cost-free solution for improving the trajectory-tracking performance in position control of mechatronic devices, with limited computational burden and, consequently, easily implementable on most commercial motion control drives.

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Section: Introductionmentioning

confidence: 99%

Experimental Assessment of Fractional-Order PDD1/2 Control of a Brushless DC Motor with Inertial Load

2020

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“…with 1 < < ρ max = (ω c2 /ω c1 ) 1/2 ; for ρ = ρ max, ω' c2 = ω' c3 = ω min . Therefore, once the ratio ρ is selected, the four corner frequencies of the PII 1/2 DD 1/2 control can be calculated by Equation (24) and then, considering that z i = −(ω' c,i ) 1/2 , it is possible to obtain the half-zeros and then the gains K p , K hi , K d , K hd by Equations ( 17)- (20). The influence of the parameter ρ on the controller frequency response will be discussed in Section 7.2.…”

Section: Pi λ D µ Frequency Responsementioning

confidence: 99%

“…In [22] PI λ D µ is applied to speed control of a chopper-fed DC motor drive. Chaotic Atom Search Optimization [23] and Flower Pollination Algorithms [24] are proposed to tune the PI λ D µ parameters for DC motor speed control. In [25] a methodology for the quantitative robustness evaluation of PI λ D µ controllers employed in DC motors is proposed.…”

Section: Introductionmentioning

confidence: 99%

Fractional-Order PII1/2DD1/2 Control: Theoretical Aspects and Application to a Mechatronic Axis

2021

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Fractional Calculus is usually applied to control systems by means of the well-known PIlDm scheme, which adopts integral and derivative components of non-integer orders λ and µ. An alternative approach is to add equally distributed fractional-order terms to the PID scheme instead of replacing the integer-order terms (Distributed Order PID, DOPID). This work analyzes the properties of the DOPID scheme with five terms, that is the PII1/2DD1/2 (the half-integral and the half-derivative components are added to the classical PID). The frequency domain responses of the PID, PIlDm and PII1/2DD1/2 controllers are compared, then stability features of the PII1/2DD1/2 controller are discussed. A Bode plot-based tuning method for the PII1/2DD1/2 controller is proposed and then applied to the position control of a mechatronic axis. The closed-loop behaviours of PID and PII1/2DD1/2 are compared by simulation and by experimental tests. The results show that the PII1/2DD1/2 scheme with the proposed tuning criterium allows remarkable reduction in the position error with respect to the PID, with a similar control effort and maximum torque. For the considered mechatronic axis and trapezoidal speed law, the reduction in maximum tracking error is −71% and the reduction in mean tracking error is −77%, in correspondence to a limited increase in maximum torque (+5%) and in control effort (+4%).

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“…Due to their higher computational complexity, these search algorithms may not be feasible for implementation on low cost control cards for onsite auto tuning control applications. Since possible advantages of FOPIDA controller to deal with high order dynamics, Puangdownreong have suggested tuning of FOPIDA controllers [25] . Particle swarm optimization algorithm was implemented for tuning FOPIDA controllers and control performance improvements were illustrated in [26] , [27] .…”

Section: Introductionmentioning

confidence: 99%

2DOF multi-objective optimal tuning of disturbance reject fractional order PIDA controllers according to improved consensus oriented random search method

Özbey

Yeroğlu

Alagöz

et al. 2020

Journal of Advanced Research

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Graphical abstract The consensus curve states a dynamic boundary that governs optimization process depending on the value of . As decreases, it implies that set point control performance is getting better, the value of consensus curve increases to meet higher disturbance rejection expectation. The logarithmic consensus coefficient is used for scaling of dynamic boundary of RDR objective. As the parameter increases and dynamic boundary increases for higher disturbance rejection performance. This leads a mechanism that increase of set point performance imposes the increase of disturbance rejection performance. The logarithmic consensus coefficient can be expressed as where is a desired optimal value of and is a desired optimal value for . Determination of the logarithmic consensus coefficient defines a consensus curve for optimal search of multi objective optimization method. The following figure illustrates a consensus curvature for the logarithmic consensus coefficient .

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Fractional Order PID Controller Design for DC Motor Speed Control System via Flower Pollination Algorithm

Cited by 24 publications

References 33 publications

Experimental Assessment of Fractional-Order PDD1/2 Control of a Brushless DC Motor with Inertial Load

Experimental Assessment of Fractional-Order PDD1/2 Control of a Brushless DC Motor with Inertial Load

Fractional-Order PII1/2DD1/2 Control: Theoretical Aspects and Application to a Mechatronic Axis

2DOF multi-objective optimal tuning of disturbance reject fractional order PIDA controllers according to improved consensus oriented random search method

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