Design of an optimal fractional-order PID controller using multi-objective GA optimization

Li, Meng; Xue, Dingyü

doi:10.1109/ccdc.2009.5191796

Cited by 44 publications

(28 citation statements)

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“…This paper proposes a multi-objective extremal optimization (MOEO)-based FOPID method called MOEO-FOPID for the fractional order frequency control of an islanded microgrid in order to improve the efficient operation of distributed generations and energy storage devices. Its superiority to other recently reported single-objective evolutionary algorithms-based FOPID [22,25], and NSGA-II-based FOPID/PID controllers [20,38] will be demonstrated by the simulation results for the typical case of an islanded microgrid.…”

Section: Introductionmentioning

confidence: 94%

“…This section presents the simulation results for an islanded microgrid in order to demonstrate the superiority of the proposed MOEO-FOPID method to the NSGA-II-based FOPID/PID [20,38] and the reported single-objective-optimization-algorithms-based FOPID method [22,25,40]. The parameters of the output saturations and rate constraints for the different elements in this microgrid are set as P FESSmax = P BESSmax = 0.11, P FCmax = 0.48, P DEGmax = 0.45, P FESSrmax = P BESSrmax = 0.05, P FCrmax = 1, and P DEGrmax = 0.5.…”

Section: Performance Comparison In Nominal Microgrid Conditionsmentioning

confidence: 99%

“…NSGA-II-FOPID/PID [20,38] I max = 500, population size NP = 30, crossover probability p c = 0.9, mutation probability p m = 1/n, distribution indexes η c = 20and η m = 20 for simulated binary crossover (SBX) and PLM MOEO-FOPID/PID I max = 500, A max = 30, q = 6…”

Section: Algorithm Parametersmentioning

confidence: 99%

“…Fractional order controllers have attracted increasing attentions recently due to their better control performance compared to traditional integer-order controllers [17][18][19][20][21][22][23][24]. Consequently, there are some recently reported frequency control methods based on fractional order proportional-integral-derivative (FOPID) controllers for islanded microgrids by using some intelligent optimization algorithms, e.g., Kriging-based surrogate modeling, called the KSM method [25], chaotic PSO based fractional order fuzzy PID controller [26].…”

Section: Introductionmentioning

confidence: 99%

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Design of a Fractional Order Frequency PID Controller for an Islanded Microgrid: A Multi-Objective Extremal Optimization Method

et al. 2017

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Abstract:Fractional order proportional-integral-derivative(FOPID) controllers have attracted increasing attentions recently due to their better control performance than the traditional integer-order proportional-integral-derivative (PID) controllers. However, there are only few studies concerning the fractional order control of microgrids based on evolutionary algorithms. From the perspective of multi-objective optimization, this paper presents an effective FOPID based frequency controller design method called MOEO-FOPID for an islanded microgrid by using a Multi-objective extremal optimization (MOEO) algorithm to minimize frequency deviation and controller output signal simultaneously in order to improve finally the efficient operation of distributed generations and energy storage devices. Its superiority to nondominated sorting genetic algorithm-II (NSGA-II) based FOPID/PID controllers and other recently reported single-objective evolutionary algorithms such as Kriging-based surrogate modeling and real-coded population extremal optimization-based FOPID controllers is demonstrated by the simulation studies on a typical islanded microgrid in terms of the control performance including frequency deviation, deficit grid power, controller output signal and robustness.

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Section: Introductionmentioning

confidence: 94%

Section: Performance Comparison In Nominal Microgrid Conditionsmentioning

confidence: 99%

Section: Algorithm Parametersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Design of a Fractional Order Frequency PID Controller for an Islanded Microgrid: A Multi-Objective Extremal Optimization Method

et al. 2017

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“…En este sentido se ha intentado aplicar diferentes técnicas para la sintonización de controles fraccionales, como el método ZieglerNichols [40][41], series de polinomios [42], algoritmos genéticos [43], enjambres de partículas [44], teoría electromagnética [45], cuantificadores dinámicos [46] y modos deslizantes [47] [48]. Sin embargo, muchas de las técnicas usadas presentan problemas por la cantidad de parámetros que se requiere calcular, lo que se traduce en alta carga computacional y altos tiempos de procesamiento, siendo esta la razón de que muchos trabajos de implementación del control fraccional se hayan hecho sobre variables o procesos de reacción lenta, tales como el control de temperatura.…”

Section: Introductionunclassified

Control PID tipo fraccional para la posición del cabezal de una unidad de CD para aplicaciones en microscopia óptica

Valencia¹,

Cardona²

2012

Iteckne

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Resumen-En este artículo se diseña un control PID tipo fraccional para la posición del cabezal de una unidad de CD que se piensa emplear en el desarrollo de un microscopio óptico motorizado. En dicha aplicación se reemplazará el disco o CD por una placa con la muestra que va a ser estudiada, y se usará el cabezal de la unidad para iluminar la muestra. Con el controlador diseñado se busca que no haya dependencia del subcó-digo escrito en un CD para determinar la posición del cabezal, para lo cual se usará un ratón de computador como sensor de posición. También se busca un control que mejore el desempeño del sistema y que sea robusto frente a las incertidumbres en el modelo de la planta, razón por la cual se empleará un control tipo fraccional (PI^λD^μ) y se ajustarán los parámetros K_p, K_i, K_d, λ, μ con cinco especificaciones de robustez. Para la sintonización del control se utiliza la toolbox de optimización de Matlab con la función fmincon. Al final del artículo se presentan los resultados en simulación, se concluye sobre la resolución obtenida, la robustez del controlador y la viabilidad del sistema de control para ser empleado en un microscopio.Palabras clave-Control de posición, Control Fraccional, Control Robusto, Microscopía óptica, ratón óptico, unidad de CD.Abstract-On this work a fractional PID controller is designed for a CD pickup head position control that is intended to use in the development of a motorized optical microscope. In such an application the disk or CD would be replaced by a plate with the sample to be studied, and the pickup head would be used to illuminate the sample. The controller is designed in such a way that there is no dependence on a CD written subcode to determine the position of the head, and for this, a computer mouse is used as a position sensor. We also look for the controller to improve the system performance and to be robust against model uncertainties of the plant, that is why we use a fractional controller PI^λ D^μ and adjust the parameters K_p, K_i, K_dλ and μ according to five robustness rules. For tuning the control we use the Matlab optimization toolbox together with fmincon function. At the end of the paper we present the simulation results, concluding about the resolution obtained, the robustness of the controller and the viability of the control system to be used in a microscope.

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Optimal controller tuning for P&O maximum power point tracking of PV systems using genetic and cuckoo search algorithms

Ahmed

Rahman

Alajmi

2020

Int Trans Electr Energ Syst

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Background: Tracking the maximum power point (MPPT) of photovoltaic (PV) systems is essential to increase the utilization efficiency. One of the most widely used algorithms is perturb and observe (P&O) technique.Methods: In this paper, tuning algorithms based on genetic algorithm (GA) and cuckoo search (CS) are proposed to provide optimal controller parameters for P&O MPPT. This optimal tuning is crucial in P&O MPPT applications of PV systems where it is difficult to tune the controllers using conventional tuning techniques to attain good performance because of the wide variations in the system parameters and its nonlinearity. The proposed tuning algorithms are used to overcome the drawbacks of the classical P&O MPPT under rapidly changing atmospheric conditions such as oscillation around the maximum power point (MPP) and low convergence speed.Results: The robustness of the algorithms is confirmed against fast varying insolation proving its ability to track the MPP in case of random and fast changing atmospheric conditions. An experimental set up of a 1 kW PV system is carried out and implemented using dSPACE DS1103 controller board and E4360 Keysight modular solar array emulator to validate the performance of the proposed optimal tuning algorithms. The measured results are in a close agreement with the simulation and the analytical system. Conclusion: Experimental and simulation results demonstrate a superior improvement in the transient and steady-state performances and in the maximum power tracking efficiency. The steady-state and the transient efficiencies of the presented work are 99.95% and 94.02% which are almost 17.59% and 10.61%, respectively superior to the classical P&O one and are 14.66% and

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Design of an optimal fractional-order PID controller using multi-objective GA optimization

Cited by 44 publications

References 3 publications

Design of a Fractional Order Frequency PID Controller for an Islanded Microgrid: A Multi-Objective Extremal Optimization Method

Design of a Fractional Order Frequency PID Controller for an Islanded Microgrid: A Multi-Objective Extremal Optimization Method

Control PID tipo fraccional para la posición del cabezal de una unidad de CD para aplicaciones en microscopia óptica

Optimal controller tuning for P&O maximum power point tracking of PV systems using genetic and cuckoo search algorithms

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