Sliding mode performance control applied to a DFIG system for a wind energy production

FatimaZohra, Mansouri; Bendjebbar, Mokhtar; Mazari, B.

doi:10.11591/ijece.v10i6.pp6139-6152

Cited by 5 publications

(8 citation statements)

References 15 publications

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“…δ is consider as unknown nonlinear function or uncertainty of dynamic, (Z) is switching [ ] function. The key objective of designing SMC is to train the appropriate state desire position according to the actual joint variables, the trucking error vector will be defined is being as [3], [5].…”

Section: Methods Of Designing Sliding Mode Control Smcmentioning

confidence: 99%

“…where is consider appositive constant [3], [6], so the sliding surface will have computed is being as:…”

Section: Methods Of Designing Sliding Mode Control Smcmentioning

confidence: 99%

“…11, No. 5, October 2021 : 3943 -3955 3944 stability [3]. Integral sliding mode controller (ISMC) was suggested in this work to boost the manipulator output to accomplish the desired tasks with high stability.…”

Section: Introductionmentioning

confidence: 99%

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Intelligent swarm algorithms for optimizing nonlinear sliding mode controller for robot manipulator

Haddad

Akkar

2021

IJECE

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This work introduces an accurate and fast approach for optimizing the parameters of robot manipulator controller. The approach of sliding mode control (SMC) was proposed as it documented an effective tool for designing robust controllers for complex high-order linear and nonlinear dynamic systems operating under uncertain conditions. In this work Intelligent particle swarm optimization (PSO) and social spider optimization (SSO) were used for obtaining the best values for the parameters of sliding mode control (SMC) to achieve consistency, stability and robustness. Additional design of integral sliding mode control (ISMC) was implemented to the dynamic system to achieve the high control theory of sliding mode controller. For designing particle swarm optimizer (PSO) and social spider optimization (SSO) processes, mean square error performances index was considered. The effectiveness of the proposed system was tested with six degrees of freedom robot manipulator by using (PUMA) robot. The iteration of SSO and PSO algorithms with mean square error and objective function were obtained, with best fitness for (SSO) =4.4876 𝑒<sup>-6</sup> and (PSO)=3.4948 𝑒<sup>-4</sup>.

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Section: Methods Of Designing Sliding Mode Control Smcmentioning

confidence: 99%

“…where is consider appositive constant [3], [6], so the sliding surface will have computed is being as:…”

Section: Methods Of Designing Sliding Mode Control Smcmentioning

confidence: 99%

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Intelligent swarm algorithms for optimizing nonlinear sliding mode controller for robot manipulator

Haddad

Akkar

2021

IJECE

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“…The need for electrical energy is increasing due to the rapidly increasing population and users' power demand for a good quality of life [1]. This continuous increase in power demand creates several challenges for the electric power companies such as overloading of the existing generating units, transmission lines, transformers, and feeders [2].…”

Section: Introductionmentioning

confidence: 99%

Dynamic response enhancement of BDFIG using vector control scheme based internal model c ontrol

Memon

Mustafa²,

Baloch³

et al. 2021

IJEECS

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Doublefed induction generator(DFIG) has shown tremendous success inwind turbines due to its flexibility and ability to regulate the active andreactive power. However, the presence of brushes and slip rings affects itsreliability, stability, and power quality. Furthermore, itdoes not providepromising outcomes in case of faults even in presence of the crowbar circuit.In contrast, thebrushless doubly fed induction generator(BDFIG) is a morereliable option for wind turbines than its mentioned counterpart due to theabsence of the brushes and slip rings. This research work as such attempts toimprove the dynamic performance of thevector control(VC)oriented powerwinding (PW) stator flux-based BDFIG by optimally selecting theproportional-integral(PI) gains throughinternalmodel control(IMC)approach. The proposed control scheme is utilized to regulate the speed,torque, and reactive power of the considered BDFIG independently. Contraryto the previous literature where the “trial and error method” is generallyutilized, the current research work uses the IMC for selecting the mostsuitable PI parameters, thus reduces the complexity, time consumption, anduncertainty in optimal selection. The considered BDFIG based wind turbinewith the proposed control scheme provides a better BDFIG control designwith an enhanced dynamic response as compared to that of the same withDFIG under identical operating conditions and system configurations.

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“…This energy is inexhaustible, clean, and does not create greenhouse gases [1]. Wind turbines usually use DFIG due to its advantages such as it can maintain the amplitude and frequency of the output voltage at a constant value, regardless of the wind speed or the speed of the turbine rotor [2][3][4]. The DFIG has two outputs: one from the stator and the other from the rotor.…”

Section: ‫المفتاحية‬ ‫الكلمات‬ : 1 Introductionmentioning

confidence: 99%

Performance of Doubly Fed Induction Generator Driven by Wind Energy at Constant Stator Power and Current

Agamy

Ellyth

Nada

et al. 2021

Journal of Al-Azhar University Engineering Sector

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This paper discusses the performance of a wind-driven doubly-fed induction generator when connected to the grid. The stator is directly connected to the grid, while the rotor side connection happens via a back-to-back converter. The performance and the steady-state analysis of the Doubly Fed Induction Generator (DFIG) when running at constant stator power and when running at constant stator current will be discussed. Laboratory experiments are performed using a testing bench for the Lucas-Nülle wind power system and the results are analyzed using Lucas-Nülle WindSim software. DFIG analysis and laboratory experiment performance were performed for two different cases; the first case is when DFIG is running at a speed lower than the synchronous speed and the second case is when DFIG is running at a speed above the synchronous speed. In both cases, the values of rotor voltage, stator current, rotor current, and the total generated power from the stator and rotor for DFIG are calculated from the analysis using MATLAB file (mfile) and compared with the practical results.

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Sliding mode performance control applied to a DFIG system for a wind energy production

Cited by 5 publications

References 15 publications

Intelligent swarm algorithms for optimizing nonlinear sliding mode controller for robot manipulator

Intelligent swarm algorithms for optimizing nonlinear sliding mode controller for robot manipulator

Dynamic response enhancement of BDFIG using vector control scheme based internal model c ontrol

Performance of Doubly Fed Induction Generator Driven by Wind Energy at Constant Stator Power and Current

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