MIC Journal

Modeling, Identification and Control

DOI

DOI INFORMATION FOR 10.4173:


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The MIC journal has implemented the DOI system for every single article published in MIC since the foundation year in 1980. The DOI prefix for MIC is 10.4173 and an individual article has been assigned a DOI on the following format: 10.4173/mic.year.no.paperno. For example, the first article published in MIC by Oddvar Hallingstad has the following DOI: 10.4173/mic.1980.1.1 and the following permanent URL http://dx.doi.org/10.4173/mic.1980.1.1. This permanent URL links back to the www.mic-journal.no website. If the MIC website is moved in the future, the DOI information will be updated to point to the new address.

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The MIC class files for pdfLaTeX found in the Author Information have commands for embedding DOI information in the PDF files. Prospective authors for future MIC articles will receive the DOI identification when the article is accepted. Authors are encouraged to embed the tag into the PDF file themselves using pdflatex prior to publication. Authors are also encouraged to embed DOI tags in their reference lists.

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DOI Forward Links to MIC for Year: 2019

 Total number of MIC articles in 2019  16
 Total number of DOI citations  55
 Average citations per article   3.44 

2019, Vol. 40, No. 4:
1.Muhammad R. U. Islam and Shaoping Bai, “Payload estimation using forcemyography sensors for control of upper-body exoskeleton in load carrying assistance”, pp. 189-198
DOI forward links to this article:
[1] Muhammad Ahsan Gull, Shaoping Bai and Thomas Bak (2020), doi:10.3390/robotics9010016
[2] Muhammad Raza Ul Islam, Asim Waris, Ernest Nlandu Kamavuako and Shaoping Bai (2020), doi:10.1177/2055668320938588
[3] Muhammad Raza Ul Islam and Shaoping Bai (2020), doi:10.3389/frobt.2020.567491
[4] Jasmine K. Proud, Daniel T. H. Lai, Kurt L. Mudie, Greg L. Carstairs, Daniel C. Billing, Alessandro Garofolini and Rezaul K. Begg (2020), doi:10.1177/0018720820957467
[5] Shaoping Bai, Muhammad R. Islam, Karl Hansen, Jacob Norgaard, Chin-Yin Chen and Guilin Yang (2022), doi:10.1007/978-3-030-69547-7_49
[6] Maria Lazzaroni, Ali Tabasi, Stefano Toxiri, Darwin G. Caldwell, Elena De Momi, Wietse van Dijk, Michiel P. de Looze, Idsart Kingma, Jaap H. van Dieen and Jesus Ortiz (2020), doi:10.1017/wtc.2020.8
[7] Shaoping Bai, M.R. Islam, Valerie Power and Leonard O ullivan (2021), doi:10.1016/j.birob.2021.100032
[8] Monica Tiboni, Alberto Borboni, Fabien Verite, Chiara Bregoli and Cinzia Amici (2022), doi:10.3390/s22030884
[9] Xiaofeng Xiong, Cao Danh Do and Poramate Manoonpong (2022), doi:10.1109/TIE.2021.3116572
[10] Stefano Massardi, David Rodriguez-Cianca, David Pinto-Fernandez, Juan C. Moreno, Matteo Lancini and Diego Torricelli (2022), doi:10.3390/s22113993
[11] Robin Otterbein, Elizabeth Jochum, Daniel Overholt, Shaoping Bai and Alex Dalsgaard (2022), doi:10.1145/3537972.3537984
[12] Pengpeng Xu, Dan Xia, Juncheng Li, Jiaming Zhou and Longhan Xie (2022), doi:10.1007/s11370-022-00435-5
[13] Marek Sierotowicz, Donato Brusamento, Benjamin Schirrmeister, Mathilde Connan, Jonas Bornmann, Jose Gonzalez-Vargas and Claudio Castellini (2022), doi:10.3389/frobt.2022.919370
[14] Muhammad Raza Ul Islam and Shaoping Bai (2022), doi:10.1016/j.bea.2022.100062
[15] Abdullah Tahir, Shaoping Bai and Ming Shen (2023), doi:10.3390/s23104863
2.Christer Dalen and David Di Ruscio, “Model-Free PI/PID Controller Tuning of Higher Order Nonlinear Dynamic Systems”, pp. 199-211
3.Ole Magnus Brastein, Bernt Lie, Carlos F. Pfeiffer and Nils-Olav Skeie, “Estimating uncertainty of model parameters obtained using numerical optimisation”, pp. 213-243
DOI forward links to this article:
[1] O.M. Brastein, A. Ghaderi, C.F. Pfeiffer and N.-O. Skeie (2020), doi:10.1016/j.enbuild.2020.110236
[2] Daniele Ronzani, Joris Gillis, Goele Pipeleers and Jan Swevers (2022), doi:10.1109/AMC51637.2022.9729282
[3] Sarah Juricic, Jeanne Goffart, Simon Rouchier, Arnaud Jay and Pierre Oberl (2022), doi:10.1016/j.enbuild.2022.112211
2019, Vol. 40, No. 3:
1.Liubomyr Vytvytskyi, Roshan Sharma and Bernt Lie, “Nonlinear observer for hydropower system”, pp. 133-142
2.Shadi Attar and Finn Haugen, “Dynamic model adaptation to an anaerobic digestion reactor of a water resource recovery facility”, pp. 143-160
DOI forward links to this article:
[1] Juan G. Rueda-Escobedo, Mihaela Sbarciog, Jaime A. Moreno, Jan Van Impe and Alain Vande Wouwer (2022), doi:10.1016/j.jprocont.2022.07.014
[2] Niloofar Raeyatdoost, Michael Bongards, Thomas Back and Christian Wolf (2023), doi:10.1016/j.jprocont.2022.11.013
[3] Xiaojun Liu, Arnaud Coutu, Stephane Mottelet, Andre Pauss and Thierry Ribeiro (2023), doi:10.3390/en16031108
[4] Hemlata Karne, Aayush Bendre and Amartya Singh (2023), doi:10.1016/j.matpr.2023.01.303
3.Ana Ionesi, M. Hossein Ramezani and Jerome Jouffroy, “On-line parameter and state estimation of an air handling unit model: experimental results using the modulating function method”, pp. 161-176
DOI forward links to this article:
[1] Radisa Jovanovic and Vladimir Zaric (2022), doi:10.2298/TSCI210825324J
4.Bjørn-Olav H. Eriksen and Morten Breivik, “Short-term ASV Collision Avoidance with Static and Moving Obstacles”, pp. 177-187
DOI forward links to this article:
[1] Bjørn Olav H. Eriksen, Morten Breivik, Erik F. Wilthil, Andreas L. Flåten and Edmund F. Brekke (2019), doi:10.1002/rob.21900
[2] Bjørn-Olav H. Eriksen, Glenn Bitar, Morten Breivik and Anastasios M. Lekkas (2020), doi:10.3389/frobt.2020.00011
[3] Hans-Christoph Burmeister and Manfred Constapel (2021), doi:10.3389/frobt.2021.739013
[4] Jianwen Li, Jalil Chavez-Galaviz, Kamyar Azizzadenesheli and Nina Mahmoudian (2023), doi:10.3390/s23073572
2019, Vol. 40, No. 2:
1.Niels C. Bender, Torben Ole Andersen and Henrik C. Pedersen, “Feasibility of Deep Neural Network Surrogate Models in Fluid Dynamics”, pp. 71-87
DOI forward links to this article:
[1] Jie Ren and Shi-Jie Cao (2020), doi:10.1016/j.buildenv.2020.106671
[2] Mireia Yurrita, Arnaud Grignard, Luis Alonso and Kent Larson (2022), doi:10.1007/978-3-030-94548-0_10
2.Daniel Hagen, Damiano Padovani and Martin Choux, “Enabling Energy Savings in Offshore Mechatronic Systems by using Self-Contained Cylinders”, pp. 89-108
DOI forward links to this article:
[1] Daniel Hagen, Damiano Padovani and Martin Choux (2019), doi:10.3390/act8040079
[2] Daniel Hagen, Damiano Padovani and Martin Choux (2019), doi:10.3390/act8040078
[3] Daniel Hagen, Damiano Padovani and Martin Choux (2020), doi:10.1109/ICIEA48937.2020.9248373
[4] Chong Shi, Yan Ren, Hesheng Tang and Leaven Romeo Mupfukirei (2021), doi:10.1088/1361-6501/abfad2
[5] Konrad Johan Jensen, Morten Kjeld Ebbesen and Michael Rygaard Hansen (2021), doi:10.3390/en14206566
[6] Shufei Qiao, Yunxiao Hao, Long Quan, Lei Ge and Lianpeng Xia (2022), doi:10.1109/ACCESS.2022.3149515
[7] D Padovani, P Fresia, M Rundo and G Altare (2022), doi:10.1088/1742-6596/2385/1/012028
[8] Jeremy Beale and Damiano Padovani (2023), doi:10.1109/ICMRE56789.2023.10106608
3.Alexander Meyer Sjøberg and Olav Egeland, “An EKF for Lie Groups with Application to Crane Load Dynamics”, pp. 109-124
DOI forward links to this article:
[1] Mark E. Petersen and Randal W. Beard (2021), doi:10.1109/CDC45484.2021.9683723
[2] Gennaro Mangiacapra, Matthew Wittal, Elisa Capello and Morad Nazari (2022), doi:10.1007/s11071-022-07293-x
[3] Lino Antoni Giefer (2021), doi:10.23919/FUSION49465.2021.9627044
[4] Weiwei Sun, Long Bai, Xinsheng Ge and Lili Xia (2022), doi:10.3390/app12104910
[5] Alexander Meyer Sjoberg and Olav Egeland (2022), doi:10.1109/TAC.2021.3121247
[6] Matthew M. Wittal, Brennan S. McCann and Morad Nazari (2023), doi:10.2514/6.2023-0700
[7] Brennan S. McCann, Morad Nazari, Matthew M. Wittal and Jeffrey Smith (2023), doi:10.2514/6.2023-2643
4.Ioannis Manganas, Torben Ole Andersen, Per Johansen and Lasse Schmidt, “Challenges in application of hybrid switched control to digital hydraulic motors”, pp. 125-132
2019, Vol. 40, No. 1:
1.Reggie Davidrajuh, Damian Krenczyk and Bozena Skolud, “Finding Clusters in Petri Nets. An approach based on GPenSIM”, pp. 1-10
DOI forward links to this article:
[1] Reggie Davidrajuh (2021), doi:10.1007/978-981-16-5203-5_9
2.Jan Fredrik Røsjordet and Geir Hovland, “Methods for Experimentally Determining Stiffness of a Multi-Axis Machining Centre”, pp. 11-25
DOI forward links to this article:
[1] Pawe Majda and Joanna Jastrz bska (2020), doi:10.1016/j.measurement.2020.108692
[2] Pawe Majda and Joanna Jastrz bska (2022), doi:10.1007/978-3-030-93377-7_8
3.Pekko Jaatinen, Jouni Vuojolainen, Niko Nevaranta, Rafal Jastrzebski and Olli Pyrhönen, “Control System Commissioning of Fully Levitated Bearingless Machine”, pp. 27-39
DOI forward links to this article:
[1] Pekko Jaatinen, Niko Nevaranta, Jouni Vuojolainen, Rafal Jastrzebski and Olli Pyrhonen (2019), doi:10.1109/IEMDC.2019.8785262
[2] Niko Nevaranta, Jouni Vuojolainen, Teemu Sillanpää and Olli Pyrhönen (2019), doi:10.1088/1757-899X/643/1/012146
[3] Niko Nevaranta, Pekko Jaatinen, Jouni Vuojolainen, Teemu Sillanpää and Olli Pyrhönen (2020), doi:10.1016/j.mechatronics.2019.102313
[4] Zebin Yang, Chao Sun, Xiaodong Sun and Yunqing Sun (2022), doi:10.1109/TIE.2021.3071712
4.Vojtech Vesely, Adrian Ilka, Ladislav Korosi and Martin Ernek, “Master-slave H-Infinity robust controller design for synchronization of chaotic systems”, pp. 41-50
DOI forward links to this article:
[1] Vojtech Vesely and Ladislav Korosi (2019), doi:10.1109/ACCS-PEIT48329.2019.9062893
[2] Yang Wang, Zhen Wang, Lingyun Kong and Hassan Zargarzadeh (2021), doi:10.1155/2021/8845553
5.Rolf Ergon “Quantitative genetics state-space modeling of phenotypic plasticity and evolution”, pp. 51-69
DOI forward links to this article:
[1] Rolf Ergon (2022), doi:10.4173/mic.2022.3.1
[2] Rolf Ergon (2022), doi:10.4173/mic.2022.4.2