• 대한전기학회
Mobile QR Code QR CODE : The Transactions of the Korean Institute of Electrical Engineers
  • COPE
  • kcse
  • 한국과학기술단체총연합회
  • 한국학술지인용색인
  • Scopus
  • crossref
  • orcid
The Transactions of the Korean Institute of Electrical Engineers

The Transactions of the Korean Institute of Electrical Engineers

ISO Journal TitleTrans. Korean. Inst. Elect. Eng.
SCImago Journal & Country Rank

Journal Search

  1. Home
  2. Archive
  3. 2026-02 (Vol.75 No.2)
  4. 10.5370/KIEE.2026.75.2.408
XML PDF INFO REF

References

1 
J. Xuan, X. Wang, D. Lu, L. Wang, 2017, Research on the safety assessment of the brushless DC motor based on the gray model, Advances in Mechanical Engineering, Vol. 9, No. 3DOI
2 
M. Weigert, 2023, Analysis of Diagnostic Capabilities for Degradation of Brushless Direct Current Motors Depending on Varying Simulation Data, Vol. 4, No. 1DOI
3 
J. S. Park, J.-H. Choi, J. Lee, 2016, Compensation Method of Position Signal Error with Misaligned Hall-Effect Sensors of BLDC Motor, Journal of Electrical Engineering and Technology, Vol. 11, No. 4, pp. 889-897DOI
4 
M. Deepak, 2022, A Review of BLDC Motor: State of Art, Advanced Control Techniques, and Applications, IEEE Access, Vol. 10, pp. 1-1DOI
5 
K.-H. Chao, C.-T. Hsieh, X.-J. Chen, 2024, A Robust Controller Based on Extension Sliding Mode Theory for Brushless DC Motor Drives, Electronics, Vol. 13, No. 20DOI
6 
P. Ubare, D. Ingole, D. N. Sonawane, 2021, Nonlinear Model Predictive Control of BLDC Motor with State Estimation, IFAC-PapersOnLine, Vol. 54, No. 6, pp. 107-112DOI
7 
W. Tan, W. Han, J. Xu, 2022, State-Space PID: A Missing Link Between Classical and Modern Control, IEEE Access, Vol. 10, pp. 116540-116553DOI
8 
T. P. Lillicrap, 2016, Continuous control with deep reinforcement learningDOI
9 
X. Hao, 2025, Deep reinforcement learning enhanced PID control for hydraulic servo systems in injection molding machines, Sci Rep, Vol. 15, No. 1DOI
10 
J. A. van Niekerk, J. D. le Roux, I. K. Craig, 2025, Reinforcement learning based automatic tuning of PID controllers in multivariable grinding mill circuits, Control Engineering Practice, Vol. 165DOI
11 
S.-Y. Noh, C.-H. Kim, 2024, SS-PID Controller Design for Maglev Conveyor Systems Based on Loop Shaping Method, pp. 23-25Google Search
12 
S.-Y. Noh, C.-H. Kim, 2025, Design of Deep RL SS-PID Controller for Constrained BLDC Motor Drive, pp. 2652-2654Google Search
13 
A. R. A. Majid, 2024, Enhancing BLDC Motor Speed Control by Mitigating Bias with a Variation Model Filter, International Journal of Advanced Computer Science and Applications (IJACSA), Vol. 15, No. 9Google Search
14 
Y. S. Park, 2016, Motor control DC, AC, BLDC motorsGoogle Search
15 
K. Ogata, 2010, Modern Control EngineeringGoogle Search
16 
Y. Ma, W. Zhu, M. G. Benton, J. Romagnoli, 2019, Continuous control of a polymerization system with deep reinforcement learning, Journal of Process Control, Vol. 75, pp. 40-47DOI
17 
S. J. D. Prince, 2024, Understanding Deep LearningGoogle Search