Adaptive fuzzy sliding mode controller design for PMLSM position control

Makhloufi, Khadidja; Bousserhane, Ismaïl Khalil; Zegnoun, Si Ahmed

doi:10.11591/ijpeds.v12.i2.pp674-684

Cited by 6 publications

(5 citation statements)

References 23 publications

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“…The constants 𝑣 1 𝑎𝑛𝑑 𝑣 2 are fixed using the genetic algorithm. They are chosen in such a way as to minimize (12). Indeed, the fitness function (the input argument of the main GA program) is defined by the error presented by the sliding surface which must be zero.…”

Section: Parameter's Optimisation Using Genetic Algorithm (Ga) For Sl...mentioning

confidence: 99%

Adaptive doubly fed induction generator’s control driven wind turbine using luenberger observer optimized by genetic algorithm

Elaimani

Essadki²,

Elmouhi³

et al. 2022

IJEECS

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The calculation of control parameters for a system control method is based on the model of the system with assumed fixed internal parameters. However, these parameters can vary greatly due to several phenomena. This paper presents an adapted control of a doubly fed induction generator machine robust against the rotor resistance variations of the machine used as a generator in wind energy conversion systems. The adaptation is ensured by a system allowing to identify in real time the value of the resistance, the system used is mainly based on a Luenberger observer. The conversion system is divided into two parts, the first mechanical part containing the turbine and the gearbox, the second electrical one consisting of a double fed induction generator, linked on the stator side directly to the grid, and on the rotor, side linked to the grid through two power electronics converters interposed with a direct current (DC) link. The machine-side converter is used to control the active and reactive powers, and the second on the grid side is used to control the DC link voltage. The converters are controlled by the sliding mode strategy, and the validity of the methods is checked by simulation using MATLAB/Simulink.

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Section: Parameter's Optimisation Using Genetic Algorithm (Ga) For Sl...mentioning

confidence: 99%

Adaptive doubly fed induction generator’s control driven wind turbine using luenberger observer optimized by genetic algorithm

Elaimani

Essadki²,

Elmouhi³

et al. 2022

IJEECS

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show abstract

“…By considering the design difficulty of the DC-DC boost converter, the successful controlling scheme should manipulate the variation in the input voltage, the desired reference voltage, and the variation of the connected load, in addition to the possibility of connected nonlinear loads. So, a robust and accurate controller such as Sliding Mode Controller SMC is necessary to have an effective converter performance (Makhloufi, Bousserhane, and Zegnoun, 2021;Sattianadan et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Robust Sliding Mode Controller Design for Boost Converter Applications

Attia,

Suan

2024

IJTech

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This paper presents detailed steps to design an effective, robust sliding mode controller for boost converter applications. Before that, the paper models a boost converter circuit during a continuous conduction mode (CCM) operation, obtains the related dynamic equations and explains the variation effects of the circuit parameters on the converter performance. The design steps of the proposed controller are illustrated, and the robustness of the controller is demonstrated in terms of maintaining output voltage stability under input voltage variations and load fluctuations. On the other hand, this paper shows a fast and accurate dynamic response of the load voltage during different reference voltages. Simulation results are collected, analyzed, and demonstrated the robustness and correctness of the proposed controller design.

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“…The primary drawback of conventional SMC is that it causes undesirable chattering issues in control, making it unsuitable for industrial applications [20]. Numerous effective control strategies, including an adaptive SMC [21], a high-order SMC [22], and an adaptive fuzzy strategy [23], have been thoroughly studied to lessen the effects of the chattering problem. As an illustration, the chattering issue was mitigated in [24] where second-order SMC was used to integrate the discontinuous switching term.…”

Section: Introductionmentioning

confidence: 99%

A tracking control design for a DC motor using robust sliding mode learning control

Hadi,

Alamili,

Abbas

2023

IJPEDS

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<p>The proposed robust sliding mode learning control (RSMLC) is a new control<br />approach that uses immediate feedback from the closed-loop system to improve tracking performance. A recursive learning technique is integrated with the sliding mode controller to ensure that the tracking error and sliding variables asymptotically converge to zero, which can be guaranteed within the framework of the proposed control approach. Moreover, the proposed controller design does not require system uncertainty and its upper limits. Thus, these benefits can be significantly simplified and mitigated by the design and implementation of RSMLC for DC motor applications. In comparison with conventional sliding mode control (CSMC), the RSMLC structure does not contain an explicit switching element, so the chattering phenomenon will be eliminated. Meanwhile, it will preserve the CSMC’s durability feature. Based on Lyapunov criteria, the stability and convergence analysis of the proposed controller were rigorously proved. Additionally, CSMC and SMLC controllers have been shown to outperform proportional integral derivative (PID) controllers in systems with nonlinear dynamics, high-order systems, or uncertainties. Finally, simulation studies of the DC<br />motor system were carried out under the proposed controller. In contrast, the CSMC simulation results are also presented for comparison purposes and to verify the validity and effectiveness of the proposed RSMLC via CSMC and PID controllers.</p>

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Adaptive fuzzy sliding mode controller design for PMLSM position control

Cited by 6 publications

References 23 publications

Adaptive doubly fed induction generator’s control driven wind turbine using luenberger observer optimized by genetic algorithm

Adaptive doubly fed induction generator’s control driven wind turbine using luenberger observer optimized by genetic algorithm

Robust Sliding Mode Controller Design for Boost Converter Applications

A tracking control design for a DC motor using robust sliding mode learning control

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