Fuzzy Logic Based Hardware Accelerator with Partially Reconfigurable Defuzzification Stage for Image Edge Detection

Kurdi, Aous H.; Grantner, Janos L.; Abdel‐Qader, Ikhlas

doi:10.1155/2017/1325493

Cited by 4 publications

(3 citation statements)

References 13 publications

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“…Controllers and some different control techniques were also investigated. [31], [32] [7], [31], [33], [34] [17], [29], [44][45][46][47][48][49][50][51][52][53][54][55] [29], [38], [59 -64] [17], [47], [48] [29], [48], [65][66][67] [16], [38][39][40] [2], [7], [41][42][43][44][45][46] [ [84][85][86][87][88][89][90][91][92][93] [ [94][95][96][97][98] […”

Section: Chapter 2 -Literature Studymentioning

confidence: 99%

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Intelligent controller for a hybrid energy storage system

Jaarsveld

Gouws

2019

2019 International Multidisciplinary Information Technology and Engineering Conference (IMITEC)

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The performance and range of electric vehicles are largely determined by the characteristics of the electrical energy storage (EES) device used. The EES should be sufficiently sized to be able to provide the necessary power and energy requirements of the vehicle. Batteries are typically energy dense, although batteries that are both energy and power dense exist, they are much more expensive. The life and usable capacity of batteries are negatively impacted by power impulses. Battery packs in electric vehicles (EV) are typically oversized to be able to provide enough power during these impulses experienced when the vehicle accelerates. Hybrid energy storage systems (HESS) have been proposed in the literature to solve these problems. HESS beneficially combines two or more EES devices with complementary characteristics. An additional EES device with a high-power density, such as an ultracapacitor, can be used as a buffer to provide power during power surges to reduce the power impulses experienced by the battery. Isolating the battery from the power impulses would allow the EV to utilize more energy dense batteries, increasing the range of the EV as well as increasing the lifetime of the utilized batteries. The research presented in this paper documents the implementation of an active HESS that combined a battery pack and an ultracapacitor bank. The implemented HESS was used to reduce the peak-power that the battery needs to provide to the load. An active topology utilising two DC/DC converters and a switch was used to implement the hybrid energy storage system. Fuzzy logic was used as a close-loop control structure to control the DC/DC converters in the topology, whilst a rule-based control strategy was used to control the operating states of the HESS. Experimental implementation of the system showed that the system was able to actively control the flow of power throughout the HESS in order to limit the power drawn from the battery to a userdefined limit. The performance of the fuzzy logic controllers was also experimentally found to be sufficient when used in conjunction with the rule-based control strategy. The system allows one to utilize batteries that are optimized for energy density seeing that the system was able to actively limit the power drawn from the battery, whilst providing the required power to the load by utilising the ultracapacitor bank. The controller and HESS were simulated in MATLAB ® /Simulink ® and practically implemented through the Simulink ® Real-Time environment with a STM32 Nucleo microcontroller. The active topology reduced the peak-power drawn from the battery by 46.05% for a pulse train load profile whilst the system reduced the peak-power drawn from the battery by 90.1% for a real-world drive cycle. The developed active HESS is not only suitable for EVs, but can be used to hybridize different energy sources, such as fuel cells, photovoltaic cells and any other EES devices that have complementary characteristics.

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Section: Chapter 2 -Literature Studymentioning

confidence: 99%

“…Fuzzy logic is aimed at providing a formalized method of reasoning which is approximate rather than exact. This allows one to characterize and control a system whose model and characterizing functions are ill-defined or not known [85]. Fuzzy logic is able to handle vague and imprecise terms and data [86].…”

Section: Fuzzy Logicmentioning

confidence: 99%

Intelligent controller for a hybrid energy storage system

Jaarsveld

Gouws

2019

2019 International Multidisciplinary Information Technology and Engineering Conference (IMITEC)

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“…The latter will be a very challenging project. Also in future research, hardware accelerators based on System-on-Chip (SoC) devices [14] will be investigated to potentially replace the main PC which is currently being used to perform the computationally extensive functions of the system. Using an SoC based system would facilitate the implementation of more complex and custom algorithms, at much higher processing rates.…”

Section: Conclusion and Future Researchmentioning

confidence: 99%

Multi-Thread Implementation of Tool Tip Tracking for Laparoscopic Surgical Box-Trainer Intelligent Performance Assessment System

Grantner¹,

Kurdi²,

Al-Gailani³

et al. 2019

ACTA POLYTECH HUNG

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Laparoscopic surgery has revolutionized medicine, yet it requires specific skills not traditionally taught to surgeons. Early in training, surgical trainees frequently use lowfidelity "box-trainers" to increase their skills. Evaluation of performance, however, is crude, frequently focusing on speed alone or subjective observations. There is a research collaboration between the Department of Electrical and Computer Engineering and the Department of Surgery, of the Homer Stryker M.D. Medical School, at WMU. The objective of this research is to develop an intelligent box-trainer system which incorporates sensory devices and high definition digital video cameras along with a fuzzy logic-based performance assessment system. Two of the key research problems of this work are the implementation of the tool tip tracking task and the associated performance assessment method. This system will more consistently evaluate trainees and their performance in real time without needing the presence of an independent observer. Using fuzzy logic to capture expert knowledge and fusing it with sensory data for performance assessment purposes is a new approach in the area of laparoscopic surgery training.

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Quality Assessment Methods to Evaluate the Performance of Edge Detection Algorithms for Digital Image: A Systematic Literature Review

Tariq

Hamzah

et al. 2021

IEEE Access

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A segmentation process is usually required in order to analyze an image. One of the available segmentation approaches is by detecting the edges on the image. Up to now, there are many edge detection algorithms that researchers have proposed. Thus, the purpose of this systematic literature review is to investigate the available quality assessment methods that researchers have utilized to evaluate the performance of the edge detection algorithms. Due to the vast number of available literature in this area, we limit our search to only open-access publications. A systematic search in five publisher websites (i.e., IEEExplore, IET digital library, Wiley, MDPI, and Hindawi) and Scopus database was carried out to gather resources that are related to the edge detection algorithms. Seventy-three publications that are about developing or comparing edge detection algorithms have been chosen. From these publication samples, we have identified 17 quality assessment methods used by researchers. Among the popular quality assessment methods are visual inspection, processing time, confusion-matrix based measures, mean square error (MSE)-based measures, and figure of merit (FOM). This survey also indicates that although most of the researchers only use a small number of test images (i.e., less than 10 test images), there are available datasets with a larger number of images for digital image segmentation that researchers can utilize.INDEX TERMS Digital image processing, edge detection algorithm, image segmentation, assessment, validation, quality measures, reviews.

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Fuzzy Logic Based Hardware Accelerator with Partially Reconfigurable Defuzzification Stage for Image Edge Detection

Cited by 4 publications

References 13 publications

Intelligent controller for a hybrid energy storage system

Intelligent controller for a hybrid energy storage system

Multi-Thread Implementation of Tool Tip Tracking for Laparoscopic Surgical Box-Trainer Intelligent Performance Assessment System

Quality Assessment Methods to Evaluate the Performance of Edge Detection Algorithms for Digital Image: A Systematic Literature Review

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