Performance of adaptive PI based on fuzzy logic for Indirect Vector Control Induction Motor drive

Zeb, Kamran; Saleem, Khurram; Mehmood, C. A.; Uddin, Waqar; Rehman, Muhammad Zia ur; Haider, Aun; Javed, Muhammad Awais

doi:10.1109/icrai.2016.7791235

Cited by 11 publications

(4 citation statements)

References 14 publications

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“…A simulation conducted in MAT-LAB/Simulink showcases the efficiency of the developed controllers in maintaining a stable output to the grid while minimizing Total Harmonic Distortion (THD). Zeb et al [15] have developed a Fuzzy-PI controller to effectively regulate the DC-link voltage in a 3 kW single-phase gridtied PV system. This research tackles the issues of voltage ripples and fluctuations in input DC voltage, as well as the reduction of DC-link capacitors.…”

Section: Literature Reviewmentioning

confidence: 99%

Modeling and Simulation of Grid-Tied Three-Phase PV System in Lahore, Pakistan

Akhtar,

Iqbal

2024

EJECE

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This research examines the implementation of grid-tied solar inverters in Lahore’s energy infrastructure, considering the city’s growing energy demands. Utilizing MATLAB/Simulink for modeling solar photovoltaic systems in Lahore’s arid climate, our study focuses on a house in Askari X housing society, Lahore, Pakistan, with a 5.1 kW load. The results demonstrate the expected system variation of a Grid-Tied PV System during grid disruptions, and the model’s consistent performance across varying irradiance conditions suggests potential economic advantages through net metering. These findings offer practical insights into the economic feasibility and dependability of grid-tied solar inverters in Lahore, highlighting their potential to contribute to the city’s energy needs.

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Section: Literature Reviewmentioning

confidence: 99%

Modeling and Simulation of Grid-Tied Three-Phase PV System in Lahore, Pakistan

Akhtar,

Iqbal

2024

EJECE

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“…The fuzzy logic controller (FLC) is reported to have the necessary speed for non-linear processes and some complex or ill-defined equations [2,3]. The use of FLC produces more robust [4] performance for speed loop control compared to the conventional proportional integral (PI) controller, especially in terms of the motor parameter variation or load disturbance [5,6]. However, the drawback of the fixed-parameter FLC is that it only produces optimum performance at the designed speed.…”

Section: Introductionmentioning

confidence: 99%

Experimental Investigations into the Behavior of Scaling Factors in a Fuzzy Logic Speed Control Induction Motor with Model Reference Adaptive Control

Ismail¹,

Talib²,

Ibrahim³

et al. 2022

ECTI-EEC

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This paper presents a self-tuning fuzzy logic speed controller (FLSC) with model reference adaptive control (MRAC) for an induction motor (IM) drive system. The MRAC is examined by output scaling the factor tuner for optimum motor speed performance. A detailed investigation is carried out on the scaling factor control of the input change error and main FLSC output increment. This proposed method utilizes seven simplified rules of the 5 × 5 matrix membership functions to minimize the computational burden and memory space limitations. All simulation work is conducted using Simulink and Fuzzy Tools in the MATLAB software and the experimental testing with the aid of a digital signal controller board, dSPACE DS1103. Based on the results, the output scaling factor makes a more significant impact on the performance effect compared to the input error scaling factor. The input change error and output SF also exhibit similar behavior, indicating that a large range of UoD tuners works well in terms of capability load rejection while a small range of UoD tuners performs well in terms of rise time. The analysis includes no-load and load tests to ascertain the overshoot percentage, rise time, and settling time for transient and steady-state conditions.

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“…The defuzzification transforms the fuzzy outcomes obtained by inference mechanism to real-time or crisp output utilizing membership functions. There are several available methods for defuzzification, i.e., mean of maximum, center of minimum, and center of gravity [36,37]. 1.…”

mentioning

confidence: 99%

“…There are several available methods for defuzzification, i.e. mean of maximum, center of minimum, and center of gravity[36,37].…”

mentioning

confidence: 99%

A New Adaptive Approach to Control Circulating and Output Current of Modular Multilevel Converter

et al. 2019

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This paper addresses the output current and circulating current control of the modular multi-level converter (MMC). The challenging task of MMCs is the control of output current and circulating current. Existing control structures for output and circulating current achieve control objectives with comparatively complex controllers and the designed parameters for the controller is also difficult. In this paper, an adaptive proportional integral (API) controller is designed to control the output current and the circulating current. The output current is regulated in α β axes while the circulating current is regulated in the a b c stationary frame to enhance MMC performance. The output and circulating current control results using an API controller are compared with the conventional proportional resonant (PR) controller in terms of transient response, stability, optimal performance, and reference tracking for results verification. The API control architecture significantly improve transient response, stability, and have excellent reference tracking capability. Moreover, it controls output current and converges the circulating current to a desired value. The control structure is designed for a three-phase MMC system, simulated and analyzed in MATLAB-Simulink.

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Performance of adaptive PI based on fuzzy logic for Indirect Vector Control Induction Motor drive

Cited by 11 publications

References 14 publications

Modeling and Simulation of Grid-Tied Three-Phase PV System in Lahore, Pakistan

Modeling and Simulation of Grid-Tied Three-Phase PV System in Lahore, Pakistan

Experimental Investigations into the Behavior of Scaling Factors in a Fuzzy Logic Speed Control Induction Motor with Model Reference Adaptive Control

A New Adaptive Approach to Control Circulating and Output Current of Modular Multilevel Converter

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