Paper Published in SCI Journal IEEE Access / Student Choi Kang Hyun (School of Electrical Engineering, Class of 2020)
- 26.02.26 / 전윤실
Choi Kang Hyun, a senior in the School of Electrical Engineering at our university, has achieved the distinction of having a research paper published in the latest issue of the SCI journal ‘IEEE Access’. The paper is titled ‘Improvement of Drone Gimbal System Performance Using a Parallel Structure of Explicit Model Predictive Control and Adaptive Neuro-Fuzzy Inference System’. ‘IEEE Access’ is an international journal publishing papers in electrical and electronic engineering and related fields.
In this research, student Choi Kang Hyun proposed a novel control structure that combines Explicit Model Predictive Control (EMPC) and Adaptive Neuro–Fuzzy Inference System (ANFIS) in parallel to simultaneously enhance the performance and stability of a drone gimbal system. First, EMPC was designed to apply pre-calculated control laws based on state variables and constraints, reducing overshoot caused by inertia. Additionally, ANFIS was designed to minimize disturbance effects by learning the relationship between disturbances and outputs and generating compensatory inputs. The paper holds academic significance as it presents a gimbal control methodology that simultaneously performs future state prediction and disturbance compensation through the parallel structure of EMPC and ANFIS.
Professor Jang Hyuk Jun from the School of Electrical Engineering, who supervised the research, added, “This study is an effective example of integrating the advantages of predictive control and intelligent learning control,” and stated, “We anticipate that intelligent control research applicable to real systems will continue to expand.”
Student Choi Kang Hyun stated, “Utilizing EMPC and ANFIS deepened my understanding of optimization theory and neural networks, and applying theoretical concepts to a real system model was a highly meaningful experience.” He also expressed his desire to “further explore the field of intelligent control using various learning algorithms.”
Meanwhile, this research was conducted with support from the Korea Research Institute for Defense Technology Planning and Advancement (KRIT) funded by the Defense Acquisition Program Administration (DAPA) and the Ministry of Education and the National Research Foundation of Korea (NRF) funded by Convergence and Open sharing System.
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Paper Published in SCI Journal IEEE Access / Student Choi Kang Hyun (School of Electrical Engineering, Class of 2020) |
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2026-02-26
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Choi Kang Hyun, a senior in the School of Electrical Engineering at our university, has achieved the distinction of having a research paper published in the latest issue of the SCI journal ‘IEEE Access’. The paper is titled ‘Improvement of Drone Gimbal System Performance Using a Parallel Structure of Explicit Model Predictive Control and Adaptive Neuro-Fuzzy Inference System’. ‘IEEE Access’ is an international journal publishing papers in electrical and electronic engineering and related fields.
In this research, student Choi Kang Hyun proposed a novel control structure that combines Explicit Model Predictive Control (EMPC) and Adaptive Neuro–Fuzzy Inference System (ANFIS) in parallel to simultaneously enhance the performance and stability of a drone gimbal system. First, EMPC was designed to apply pre-calculated control laws based on state variables and constraints, reducing overshoot caused by inertia. Additionally, ANFIS was designed to minimize disturbance effects by learning the relationship between disturbances and outputs and generating compensatory inputs. The paper holds academic significance as it presents a gimbal control methodology that simultaneously performs future state prediction and disturbance compensation through the parallel structure of EMPC and ANFIS.
Professor Jang Hyuk Jun from the School of Electrical Engineering, who supervised the research, added, “This study is an effective example of integrating the advantages of predictive control and intelligent learning control,” and stated, “We anticipate that intelligent control research applicable to real systems will continue to expand.”
Student Choi Kang Hyun stated, “Utilizing EMPC and ANFIS deepened my understanding of optimization theory and neural networks, and applying theoretical concepts to a real system model was a highly meaningful experience.” He also expressed his desire to “further explore the field of intelligent control using various learning algorithms.”
Meanwhile, this research was conducted with support from the Korea Research Institute for Defense Technology Planning and Advancement (KRIT) funded by the Defense Acquisition Program Administration (DAPA) and the Ministry of Education and the National Research Foundation of Korea (NRF) funded by Convergence and Open sharing System.
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