Performance Enhancement of UPQC Using Takagi–Sugeno Fuzzy Logic Controller

Haq, S. Shamshul; Lenine, D.; Lalitha, S. V. N. L.

doi:10.1007/s40815-021-01095-w

Cited by 6 publications

(2 citation statements)

References 23 publications

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“…It was assumed that there is a point P(X W , Y W , Z W ) in the world coordinate system, P(X C , Y C , Z C ) in the camera coordinate system [27] , and P(X L , Y L , Z L ) in the manipulator coordinate system. To simplify the calculation, the world coordinate system is set to coincide with the manipulator coordinate system, and the origin is the fixed joint point of the manipulator, thus, the corresponding relationship can be expressed as Equation (10).…”

Section: Lettuce Visual Velocimetry Modelmentioning

confidence: 99%

“…The YOLO algorithm conducts object classification and candidate box prediction directly, and the detection speed is significantly improved. The SSD algorithm combines the advantages of the YOLO [9] algorithm; the faster R-CNN algorithm proposes feature maps of different scales to detect objects; and CNN directly makes predictions [10] . This kind of algorithm has a robust real-time performance, which promotes the application of object detection algorithms based on deep learning in industrial applications.…”

Section: Introductionmentioning

confidence: 99%

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Intelligent sorting method for assembly line based on visual positioning and model predictive control of robotic arm

Zhang,

Lu,

Jian

et al. 2023

International Journal of Agricultural and Biological Engineering

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The existing steering device in the fruit and vegetable packaging assembly line cannot adjust the attitude of lettuce to a unified attitude, affecting the input and packaging process of the packaging machine. This study proposes an intelligent assembly line sorting method based on the visual positioning and model predictive control of a robotic arm. First, lightweight improvement based on the YOLOv5 is realized, the lettuce stalk in the background of the conveyor belt is promptly identified, the image of the lettuce stalk in the anchor box area is processed, and the edge contour point set is determined to extract the pixel coordinates of the optimal grasp point and mirror inclination angle of the lettuce. For the intelligent assembly line system, a robot arm kinematics model is constructed and the robot kinematics inverse solutions are calculated. Additionally, the lettuce movement speeds are dynamically measured by the vision system. A combination of the model prediction control, dynamic tracking, and rapid sorting of the lettuce by the robot claw is realized. The results show that the average detection time of a single frame image in the visual positioning part is 0.014 s, which is reduced by 50%; the accuracy and recall are 98% and 95%, respectively. The detection time is significantly reduced by ensuring accuracy. Within the current speed range of the packaging assembly line conveyor belt, the manipulator can grasp lettuce at different speeds stably and fast; the average axial error, average radial error, and adjusted average inclination angle error are 0.71 cm, 1.02 cm, and 3.79°, respectively, verifying the high efficiency and stability of the model. The proposed method of this study enables application in the intelligent sorting operation of industrial assembly lines

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Section: Lettuce Visual Velocimetry Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Intelligent sorting method for assembly line based on visual positioning and model predictive control of robotic arm

Zhang,

Lu,

Jian

et al. 2023

International Journal of Agricultural and Biological Engineering

View full text Add to dashboard Cite

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Comparison of THD in grid connected power system with novel fuzzy logic controller tuned UPQC and without UPQC connected to grid

Kumar,

Priya

2024

Fifth International Conference on Applied Sciences: Icas2023

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Performance enhancement of UPQC based on optimized GBSSA hybrid fuzzy controller with EPLL

Monikandan¹,

Kumar²

2022

IFS

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In this research, UPQC (Unified Power Quality Conditioner) with optimized hybrid fuzzy controller based GBSSA (Gaussian Barebone Salp Swarm Algorithm) with EPLL (Enhanced Phase Locked Loop) have been proposed for power quality enhancement in power distribution networks. Using the proposed method, the difficulties in major of the power distribution system networks can be solved, related to power quality issues. GBSSA has been employed in this research, to improve solution accuracy and optimization efficiency. Given that, it is permissible to add some extra time cost to acquire a better solution, based on the Non-Free Lunch (NFL) theory, and that the time consumption of function evaluation is rather large, when addressing actual optimization problems, the extra time consumption can be overlooked to some extent. The EPLL control method improves the standard PLL, by reducing its fundamental flaw, which is the occurrence of main frequency errors, as well as double frequency errors. It controls the DC-bus voltage of unified power quality conditioners, during supply voltage and load voltage turbulences. The proposed UPQC control technique has been found to be resilient, to a variety of source and load perturbations, including unbalanced, transient distorted supply, voltage sag, unbalanced load and voltage swell. The proposed optimized GBSSA hybrid fuzzy controller with EPLL has been proven to be more effective in reducing the THD (Total Harmonic Distortion) to 3.22% . Moreover, comparative analysis with a conventional TSF-PLL has been performed with that of Takagi-Sugeno fuzzy controller and implemented using MATLAB (MATrix Laboratory).

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Performance Enhancement of UPQC Using Takagi–Sugeno Fuzzy Logic Controller

Cited by 6 publications

References 23 publications

Intelligent sorting method for assembly line based on visual positioning and model predictive control of robotic arm

Intelligent sorting method for assembly line based on visual positioning and model predictive control of robotic arm

Comparison of THD in grid connected power system with novel fuzzy logic controller tuned UPQC and without UPQC connected to grid

Performance enhancement of UPQC based on optimized GBSSA hybrid fuzzy controller with EPLL

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