Robust Adaptive Supervisory Fractional Order Controller for Optimal Energy Management in Wind Turbine with Battery Storage

Meghni, Billel; Dib, Djalel; Azar, Ahmad Taher; Ghoudelbourk, Sihem; Saadoun, A.

doi:10.1007/978-3-319-50249-6_6

Cited by 48 publications

(17 citation statements)

References 67 publications

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“…This complementary sensitivity function is obtained to derive the K ∞ gain matrix and, later, the gain K(s) is obtained with the loop shaping design procedure as shown in step 2 and 3. Remember that in the robust loop shaping design given in ( 7), (8), and ( 9), the max and γ min are found obtaining the coprime factorization of the plant to be shaped G(s) as presented in Figures 2 and 3.…”

Section: H ∞ Loop Shaping Design Proceduresmentioning

confidence: 99%

“…In the SISO system, the H-infinity controller is found by synthesizing the performance index to find the desired controller meeting the robust stability and robust performance conditions. Meanwhile, the suitable controller and gain matrices are obtained for the MIMO case, similar to in the SISO case, synthesizing the selected performance index [8].…”

Section: Introductionmentioning

confidence: 99%

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Robust H∞ Loop Shaping Controller Synthesis for SISO Systems by Complex Modular Functions

Azar

Serrano

Kamal

2021

MCA

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In this paper, a loop shaping controller design methodology for single input and a single output (SISO) system is proposed. The theoretical background for this approach is based on complex elliptic functions which allow a flexible design of a SISO controller considering that elliptic functions have a double periodicity. The gain and phase margins of the closed-loop system can be selected appropriately with this new loop shaping design procedure. The loop shaping design methodology consists of implementing suitable filters to obtain a desired frequency response of the closed-loop system by selecting appropriate poles and zeros by the Abel theorem that are fundamental in the theory of the elliptic functions. The elliptic function properties are implemented to facilitate the loop shaping controller design along with their fundamental background and contributions from the complex analysis that are very useful in the automatic control field. Finally, apart from the filter design, a PID controller loop shaping synthesis is proposed implementing a similar design procedure as the first part of this study.

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Section: H ∞ Loop Shaping Design Proceduresmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Robust H∞ Loop Shaping Controller Synthesis for SISO Systems by Complex Modular Functions

Azar

Serrano

Kamal

2021

MCA

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“…Main aspect is to balance the exploration and exploitation during the process in order to reach global optimal solution. These decades many algorithms are applied to solve the various engineering problems effectively (Azar and Vaidyanathan, 2015a, 2016Azar and Zhu, 2015;Azar and Serrano, 2015aBoulkroune et al, 2016aBoulkroune et al, , 2016bGhoudelbourk et al, 2016;Meghni et al, 2017aMeghni et al, , 2017bMeghni et al, , 2017cAzar et al, 2017aAzar et al, , 2017bAzar et al, , 2017cAzar et al, , 2017dAzar, 2010aAzar, , 2010bAzar, , 2012Mekki et al, 2015;, 2016c, 2016d, 2016e, 2016f, 2016g, 2017ab, 2017cZhu and Azar, 2015;Grassi et al, 2017;Ouannas et al, 2016aOuannas et al, , 2016bOuannas et al, , 2017aOuannas et al, , 2017bOuannas et al, , 2017cOuannas et al, , 2017dSingh et al, 2017;Wang et al, 2017;Soliman et al, 2017;Tolba et al, 2017). In this work Henry's Law (HLG) based -soluble gas optimization algorithm, Mobula alfredi optimization (MAO) algorithm and balanced condition algorithm (BCA) has been designed to solve the optimal reactive power problem.…”

Section: Introductionmentioning

confidence: 99%

Reduction of power loss by Henry's law-based soluble gas, mobula alfredi and balanced condition optimization algorithms

Lenin

2021

COMPEL

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Purpose Purpose of this paper are Real power loss reduction, voltage stability enhancement and minimization of Voltage deviation. Design/methodology/approach In HLG approach as per Henry gas law sum of gas dissolved in the liquid is directly proportional to the partial pressure on above the liquid. Gas dissolving in the liquid which based on Henry gas law is main concept to formulate the proposed algorithm. Populations are divided into groups and all the groups possess the similar Henry constant value. Exploration and exploitation has been balanced effectively. Ranking and position of the worst agents is done in order to avoid the local optima. Then in this work Mobula alfredi optimization (MAO) algorithm is projected to solve optimal reactive power problem. Foraging actions of Mobula alfredi has been imitated to design the algorithm. String foraging, twister foraging and backward roll foraging are mathematically formulated to solve the problem. In the entire exploration space the Mobula alfredi has been forced to discover new regions by assigning capricious position. Through this approach, exploration competence of the algorithm has been improved. In all iterations, the position of the Mobula alfredi has been updated and replaced with the most excellent solution found so far. Exploration and exploitation capabilities have been maintained sequentially. Then in this work balanced condition algorithm (BCA) is projected to solve optimal reactive power problem. Proposed BCA approach based on the conception in physics- on the subject of the mass; incoming, exit and producing in the control volume. Preliminary population has been created based on the dimensions and number of particles and it initialized capriciously in the exploration space with minimum and maximum concentration. Production control parameter and Production probability utilized to control the exploration and exploitation. Findings Proposed Henry's Law based -soluble gas optimization (HLG) algorithm, Mobula alfredi optimization (MAO) algorithm and BCA are evaluated in IEEE 30 bus system with L-index (Voltage stability) and also tested in standard IEEE 14, 30, 57, 118, 300 bus test systems without L- index. Real power loss minimization, voltage deviation minimization, and voltage stability index enhancement has been attained. Originality/value For the first time Henry's Law based -soluble gas optimization (HLG) algorithm, Mobula alfredi optimization (MAO) algorithm and BCA is projected to solve the power loss reduction problem.

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“…Although the subject is as old as the conventional calculus, it did not attract enough attention until recent decades. Nowadays, it has been known that many systems in interdisciplinary fields, such as viscoelastic materials, (Bagley and Calico, 1991) electrode electrolyte polarisation (Ichise et al, 1971), thermoelectric systems (Ezzat and El-Karamany, 2012), finance systems (Laskin, 2000), dielectric polarisation (Sun et al, 1984), control systems (Sun et al, 1984;Ghoudelbourk et al, 2016;Azar et al, 2017aAzar et al, , 2017bAzar et al, , 2017cAzar et al, , 2017dAzar et al, , 2018aAzar et al, , 2018bAzar and Serrano, 2018), synchronisation (Alain et al, 2018;Soliman et al, 2017;Tolba et al, 2017aTolba et al, , 2017b, boundary layer effects in ducts, electromagnetic waves, signal processing, and bio-engineering, can be elegantly described by fractional differential derivatives (Meghni et al, 2017a(Meghni et al, , 2017b(Meghni et al, , 2017c and the references therein. The fractional calculus provides an effective tool for the description of the memory and hereditary properties of various materials and processes.…”

Section: Introductionmentioning

confidence: 99%

Stability analysis and robust synchronisation of fractional-order modified Colpitts oscillators

Alain

Azar

Kengne

et al. 2020

IJAAC

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Based on the stability theory of the fractional order system, the dynamic behaviours of the uncertain Colpitts oscillator with fractional order-derivative is studied. Furthermore, based on the extended bounded real lemma, the robust controller is obtained using the drive-response synchronisation concept together with the Lyapunov stability theory formulated using the fractional Lyapunov direct method where the fractional-order q belongs to 0 < q < 1. In order to bring out the dynamic behaviour of this system, their phase portraits, the bifurcation diagrams and the Lyapunov exponent are simulated. Moreover, in this work, an approximated solution for both systems to show that the solution of such a system can be represented as a simple power-series function is provided. This study equally provides a systematic procedure to highlight the simplicity and flexibility of the suggested control approach. Simulations with both parameters uncertainty and external disturbance show the applicability and the efficiency of the proposed scheme.

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Robust Adaptive Supervisory Fractional Order Controller for Optimal Energy Management in Wind Turbine with Battery Storage

Cited by 48 publications

References 67 publications

Robust H∞ Loop Shaping Controller Synthesis for SISO Systems by Complex Modular Functions

Robust H∞ Loop Shaping Controller Synthesis for SISO Systems by Complex Modular Functions

Reduction of power loss by Henry's law-based soluble gas, mobula alfredi and balanced condition optimization algorithms

Stability analysis and robust synchronisation of fractional-order modified Colpitts oscillators

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