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Dr. Farzin Piltan

Farzin Piltan is a Research Professor at the Ulsan Industrial Artificial Intelligence (UIAI) Lab., Department of Electrical and Computer Engineering, University of Ulsan, Ulsan, South Korea. From 2004-2017, Dr. Piltan was the Head of Mechatronics, Intelligent System, and Robotics Laboratory at the Iranian Center of Advance Science and Technology (IRAN SSP). IRAN SSP is an independent research center specializing in research projects related to control and automation engineering, artificial intelligence, intelligent nonlinear control, electronic engineering, and robotics. Dr. Piltan has authored or co-authored more than 205 papers in academic journals, conferences and book chapters. He is also an editorial board member of several academic journals. He has served as a reviewer for several recognized journals and conferences. His research interests include electronics, computers, and control engineering with expertise in the areas of analysis of data, artificial intelligence, (machine/deep) learning control algorithm, robotics, and advance digital electronics.

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Recent Publications [Journal Papers/ Chapters]

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Journal Papers

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  • 2022

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  1.  Farzin Piltan, Toma, Rafia Nishatand, Dongkoo Shon, Kichang Im, Hyun-Kyun Choi, Dae-Seung Yoo, and Jong-Myon Kim. "Strict-Feedback Backstepping Digital Twin and Machine Learning Solution in AE Signals for Bearing Crack Identification." Sensors 22, no. 2 (2022): 539. Sensors [SCIE-IF:3.275].  https://doi.org/10.3390/s22020539

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  • 2021​

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  1. Toma, Rafia Nishat, Farzin Piltan, and Jong-Myon Kim. "A Deep Autoencoder-Based Convolution Neural Network Framework for Bearing Fault Classification in Induction Motors." Sensors 21, no. 24 (2021): 8453. Sensors [SCIE-IF:3.275].  https://doi.org/10.3390/s21248453

  2. Farzin Piltan, and Jong-Myon Kim. "Crack Size Identification for Bearings Using an Adaptive Digital Twin" Sensors, 2021, 21, no. 15: 5009. [SCIE-IF:3.576]. https://doi.org/10.3390/s21155009

  3. Farzin Piltan, and Jong-Myon Kim. Leak detection and localization for pipelines using multivariable fuzzy learning backstepping. Journal of Intelligent & Fuzzy Systems Preprint: 1-12. [SCIE-IF:1.851]. https://doi.org/10.3233/JIFS-219197

  4. Farzin Piltan, and Kim, J. M. Bearing Anomaly Recognition Using an Intelligent Digital Twin Integrated with Machine Learning. Appl. Sci. 2021, 11, 4602. [SCIE, IF: 2.474], https://doi.org/10.3390/app11104602

  5. Farzin Piltan, Bach Phi Duong, and Kim, J. M. Deep Learning-Based Adaptive Neural-Fuzzy Structure Scheme for Bearing Fault Pattern Recognition and Crack Size Identification. Sensors. 2021; 21(6):2102. [SCIE-IF:3.275].  https://doi.org/10.3390/s21062102

  6. Farzin Piltan, and Kim, J. M. Fault Diagnosis of Bearings Using an Intelligence-Based Autoregressive Learning Lyapunov Algorithm. International Journal of Computational Intelligence Systems. 2021,01; doi: https://doi.org/10.2991/ijcis.d.201228.002 [SCIE-IF:1.838].     https://doi.org/10.2991/ijcis.d.201228.002

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  • 2020

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  1. Prosvirin AE, Farzin Piltan, and Kim, J. M. Blade Rub-Impact Fault Identification Using Autoencoder-Based Nonlinear Function Approximation and a Deep Neural Network. Sensors, 2020, 20 (21), 6265. [SCIE-IF:3.275].  https://doi.org/10.3390/s20216265

  2. Prosvirin AE, Farzin Piltan, Kim JM. Hybrid Rubbing Fault Identification Using a Deep Learning-Based Observation Technique. IEEE Trans Neural Netw Learn Syst. 2020 Oct 8;PP. doi: 10.1109/TNNLS.2020.3027160. Epub ahead of print. PMID: 33031043. [SCI-IF:8.793]

  3. Farzin Piltan, and Kim, J. M. Bearing Fault Identification Using Machine Learning and Adaptive Cascade Fault Observer  . Applied Sciences, 2020, 10, 5827. [SCIE-IF=2.474]. https://doi.org/10.3390/app10175827 

  4. Farzin Piltan; Prosvirin, A.E.; Jong-Myon Kim. Robot Manipulator Active Fault-Tolerant Control Using Machine Learning-based Automated Robust Hybrid Observer. Journal of Intelligent and Fuzzy Systems, 2020, 1-21. [SCIE-IF:1.851] https://doi.org/10.3233/JIFS-189109

  5. Farzin Piltan, and Kim, J. M. Hybrid Fault Diagnosis of Bearings: Adaptive Fuzzy Orthonormal-ARX Robust Feedback Observer. Applied Sciences, 2020, 10, 3587. [SCIE-IF=2.217]. https://doi.org/10.3390/app10103587

  6. Farzin Piltan, Prosvirin, A. E, Muhammad Sohaib, Belem Saldivar, and Kim, J. M. An SVM-Based Neural Adaptive Variable Structure Observer for Fault Diagnosis and Fault-Tolerant Control of a Robot Manipulator. Applied Sciences, 2020, 10, 1344. [SCIE-IF=2.217]. https://doi.org/10.3390/app10041344

  7. Farzin Piltan, and  Kim, J.-M. Advanced Fuzzy-Based Leak Detection and Size Estimation for Pipelines. Journal of Intelligent & Fuzzy Systems 2020, 38, 947-961. [SCIE, Impact Factor: 1.637]. https://doi.org/10.3233/JIFS-179461

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  • 2019

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  1. Farzin Piltan, Prosvirin, A. E; Jeong, I; Im, K; and Kim, J. M. Rolling Element Bearing Fault Diagnosis Using Advanced Machine Learning-Based Observer. Applied Sciences, 2019, 9(24), 5404. [SCIE-IF=2.217]. https://doi.org/10.3390/app9245404

  2. Farzin Piltan; Kim, C.-H.; Kim, J.-M. Adaptive Fuzzy-Based Fault-Tolerant Control of a Continuum Robotic System for Maxillary Sinus Surgery. Applied Sciences 2019, 9 (12), 2490. [SCIE-IF=2.217] https://doi.org/10.3390/app9122490

  3. Farzin Piltan; Kim, C.-H.; Kim, J.-M. Advanced Adaptive Fault Diagnosis and Tolerant Control for Robot Manipulators. Energies 2019, 12, 1281. [SCIE, Impact Factor: 2.676]. https://doi.org/10.3390/en12071281

  4. Farzin Piltan, Shahnaz TayebiHaghighi, Somayeh Jowkar, Hossein Rashidi Bod, Amirzubir Sahamijoo, Jeong-Seok Heo, "A Novel Intelligent ARX-Laguerre Distillation Column Estimation Technique", International Journal of Intelligent Systems and Applications (IJISA), Vol.11, No.4, pp.52-60, 2019. DOI: 10.5815/ijisa.2019.04.05 [Scopus-SJR=0.18]  https://doi.org/10.5815/ijisa.2019.04.05

  5. Farzin Piltan, Shahnaz TayebiHaghighi, Amirzubir Sahamijoo, Hossein Rashidi Bod, Somayeh Jowkar, Jong-Myon Kim, "Adaptive Finite Time Convergence Fuzzy ARX-Laguerre System Estimation", International Journal of Intelligent Systems and Applications (IJISA), Vol.11, No.5, pp.27-35, 2019. DOI: 10.5815/ijisa.2019.05.04 [Scopus-SJR=0.18]    https://doi.org/10.5815/ijisa.2019.05.04                         

  6. Farzin Piltan, and Jong-Myon Kim. "Nonlinear Extended-state ARX-Laguerre PI Observer Fault Diagnosis of Bearings." Applied Sciences 9, no. 5 (2019): 888. (SCIE, Impact Factor: 2.217). https://doi.org/10.3390/app9050888

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  • 2018

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  1. Farzin Piltan, and Jong-Myon Kim. "Bearing Fault Diagnosis Using an Extended Variable Structure Feedback Linearization Observer." Sensors 18.12 (2018): 4359. (SCIE, Impact Factor: 3.03). https://doi.org/10.3390/s18124359

  2. Farzin Piltan, and Jong-Myon Kim. "Bearing fault diagnosis by a robust higher-order super-twisting sliding mode observer." Sensors 18, no. 4 (2018): 1128.(SCIE, Impact Factor: 3.03). https://doi.org/10.3390/s18041128

  3. Shahnaz Tayebihaghighi, Farzin Piltan, and Jong-Myon Kim. "Control of an Uncertain Robot Manipulator Using an Observation-based Modified Fuzzy Sliding Mode Controller." International Journal of Intelligent Systems and Applications 10, no. 3 (2018): 41.[Scopus-SJR=0.18] https://doi.org/10.5815/ijisa.2018.03.05

  4.  Shahnaz Tayebi-Haghighi, Farzin Piltan, and Jong-Myon Kim. "Robust Composite High-Order Super-Twisting Sliding Mode Control of Robot Manipulators." Robotics 7, no. 1 (2018): 13.[Scopus-SJR=0.48] https://doi.org/10.3390/robotics7010013

  5. Farzin Piltan, Jong-Myon Kim,” FPGA-Based ARX-Laguerre PIO Fault Diagnosis in Robot Manipulator”, Advances in Robotics Research, 2(1), (2018):  99-112.[Scopus] https://doi.org/10.12989/arr.2018.2.1.099

  6. Niloofar Mirzavand, Farzin Piltan, Jong-Myon Kim, “Intelligent Control of an Uncertain Distillation Column Using a Multivariable Filter Decoupling-based PID Like Fuzzy Controller”, International Journal of Control and Automation,11(1),  (2018): 99-112[Scopus] https://doi.org/10.14257/ijca.2018.11.1.09

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Chapters

  1. Farzin Piltan, Kim JM.  Crack Localization of Pipelines Using Machine Learning and Fuzzy Digital Twin. 2021 International Conference on Information and Communication Technology Convergence (ICTC-2021), IEEE, 2021. Crack Localization of Pipelines Using Machine Learning and Fuzzy Digital Twin | IEEE Conference Publication | IEEE Xplore

  2. Farzin Piltan, Kim JM. (2022) Smart Digital Twin-Based Bearing Fault Pattern Recognition. In: Kahraman C., Cebi S., Cevik Onar S., Oztaysi B., Tolga A.C., Sari I.U. (eds) Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation. INFUS 2021. Lecture Notes in Networks and Systems, vol 307. Springer, Cham. https://doi.org/10.1007/978-3-030-85626-7_1

  3. Farzin Piltan, Kim JM. (2022) Self-Tuning Intelligence Digital Twin for Bearing Pattern Recognition. In: Kahraman C., Cebi S., Cevik Onar S., Oztaysi B., Tolga A.C., Sari I.U. (eds) Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation. INFUS 2021. Lecture Notes in Networks and Systems, vol 307. Springer, Cham. https://doi.org/10.1007/978-3-030-85626-7_7

  4. Farzin Piltan, Kim JM. (2022) State Prediction of Chaotic Time-Series Systems Using Autoregressive Integrated with Adaptive Network-Fuzzy. In: Kahraman C., Cebi S., Cevik Onar S., Oztaysi B., Tolga A.C., Sari I.U. (eds) Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation. INFUS 2021. Lecture Notes in Networks and Systems, vol 308. Springer, Cham. https://doi.org/10.1007/978-3-030-85577-2_49

  5. Farzin Piltan, and Jong-Myon Kim. "Machine Learning-Based Robust Feedback Observer for Fault Diagnosis in Bearings." Springer, 2021. (Best Support-Research Award) https://doi.org/10.1007/978-3-030-51156-2_129

  6. Farzin Piltan, and Jong-Myon Kim. "SVM-Based Hybrid Robust PIO Fault Diagnosis for Bearings." Springer, 2021. (Best Support-Research Award) https://doi.org/10.1007/978-3-030-51156-2_99

  7. Farzin Piltan, and Jong-Myon Kim. "Pipeline Leak Detection and Estimation Using Fuzzy-Based PI Observer." Springer, 2020, pp. 1122-1129. (Best Research Award). https://doi.org/10.1007/978-3-030-23756-1_132

  8. Farzin Piltan, and Jong-Myon Kim. "Advanced Fuzzy Observer-Based Fault Identification for Robot Manipulators." Springer, 2020, pp. 141-148. (Best research award). https://doi.org/10.1007/978-3-030-23756-1_19

  9. Farzin Piltan, Manjurul Islam, and Jong-Myon Kim. "Input-Output Fault Diagnosis in Robot Manipulator Using Fuzzy LMI-Tuned PI Feedback Linearization Observer Based on Nonlinear Intelligent ARX Model." Springer, 2019, pp. 305-315. https://doi.org/10.1007/978-981-13-0341-8_28

  10. Farzin Piltan, and Jong-Myon Kim. "Fault Diagnosis of a Wireless Sensor Network Using a Hybrid Method." Springer, 2019, pp. 133-142. https://doi.org/10.1007/978-981-13-5907-1_14

  11. Farzin Piltan, Muhammad Sohaib, and Jong-Myon Kim. "Fault Diagnosis of a Robot Manipulator Based on an ARX-Laguerre Fuzzy PID Observer." Springer, 2019, pp. 393-407. https://doi.org/10.1007/978-3-319-78452-6_33

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