메뉴 건너뛰기




Volumn 62, Issue 1, 2015, Pages 657-667

Data-based techniques focused on modern industry: An overview

Author keywords

Complicated industrial applications; data based techniques; monitoring and control; overview

Indexed keywords

INDUSTRIAL ELECTRONICS;

EID: 84919906918     PISSN: 02780046     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIE.2014.2308133     Document Type: Article
Times cited : (898)

References (86)
  • 2
    • 35548968908 scopus 로고    scopus 로고
    • Data-based process monitoring, process control, quality improvement: Recent developments and applications in steel industry
    • Jan
    • M. Kano and Y. Nakagawa, "Data-based process monitoring, process control, quality improvement: Recent developments and applications in steel industry," Comput. Chem. Eng., vol. 32, no. 1, pp. 12-24, Jan. 2008.
    • (2008) Comput. Chem. Eng. , vol.32 , Issue.1 , pp. 12-24
    • Kano, M.1    Nakagawa, Y.2
  • 3
    • 67349089877 scopus 로고    scopus 로고
    • Data-driven soft sensors in the process industry
    • Apr
    • P. Kadlec, B. Gabrys, and S. Strandt, "Data-driven soft sensors in the process industry," Comput. Chem. Eng., vol. 33, no. 4, pp. 795-814, Apr. 2009.
    • (2009) Comput. Chem. Eng. , vol.33 , Issue.4 , pp. 795-814
    • Kadlec, P.1    Gabrys, B.2    Strandt, S.3
  • 4
    • 84877574535 scopus 로고    scopus 로고
    • Optimal input design for direct data-driven tuning of model-reference controllers
    • Jun
    • S. Formentin, A. Karimi, and S. M. Savaresi, "Optimal input design for direct data-driven tuning of model-reference controllers," Automatica, vol. 49, no. 6, pp. 1874-1882, Jun. 2013.
    • (2013) Automatica , vol.49 , Issue.6 , pp. 1874-1882
    • Formentin, S.1    Karimi, A.2    Savaresi, S.M.3
  • 5
    • 84866132201 scopus 로고    scopus 로고
    • Data-driven monitoring for stochastic systems and its application on batch process
    • Jul
    • S. Yin, S. X. Ding, A. H. Abandan Sari, and H. Hao, "Data-driven monitoring for stochastic systems and its application on batch process," Int. J. Syst. Sci., vol. 44, no. 7, pp. 1366-1376, Jul. 2013.
    • (2013) Int. J. Syst. Sci. , vol.44 , Issue.7 , pp. 1366-1376
    • Yin, S.1    Ding, S.X.2    Abandan Sari, A.H.3    Hao, H.4
  • 6
    • 84871762750 scopus 로고    scopus 로고
    • Computer communication within industrial distributed environment-A survey
    • Feb
    • P. Gaj, J. Jasperneite, andM. Felser, "Computer communication within industrial distributed environment-A survey," IEEE Trans. Ind. Informat., vol. 9, no. 1, pp. 182-189, Feb. 2013.
    • (2013) IEEE Trans. Ind. Informat. , vol.9 , Issue.1 , pp. 182-189
    • Gaj, P.1    Jasperneite, J.2    Felser, M.3
  • 8
    • 84879121354 scopus 로고    scopus 로고
    • Security analysis and improvement of a secure and distributed reprogramming protocol for wireless sensor networks
    • Nov
    • D. He, C. Chen, S. Chan, J. Bu, and L. Yang, "Security analysis and improvement of a secure and distributed reprogramming protocol for wireless sensor networks," IEEE Trans. Ind. Electron., vol. 60, no. 11, pp. 5348-5354, Nov. 2013.
    • (2013) IEEE Trans. Ind. Electron. , vol.60 , Issue.11 , pp. 5348-5354
    • He, D.1    Chen, C.2    Chan, S.3    Bu, J.4    Yang, L.5
  • 10
    • 77957298441 scopus 로고    scopus 로고
    • Fault detection based on kernel principal component analysis
    • Nov
    • V. H. Nguyen and J.-C. Golinval, "Fault detection based on kernel principal component analysis," Eng. Struct., vol. 32, no. 11, pp. 3683-3691, Nov. 2010.
    • (2010) Eng. Struct. , vol.32 , Issue.11 , pp. 3683-3691
    • Nguyen, V.H.1    Golinval, J.-C.2
  • 11
    • 9744237208 scopus 로고    scopus 로고
    • Multiple-fault diagnosis of the Tennessee Eastman process based on system decomposition and dynamic PLS
    • G. Lee, C. Han, and E. S. Yoon, "Multiple-fault diagnosis of the Tennessee Eastman process based on system decomposition and dynamic PLS," Ind. Eng. Chem. Res., vol. 43, no. 25, pp. 8037-8048, 2004.
    • (2004) Ind. Eng. Chem. Res. , vol.43 , Issue.25 , pp. 8037-8048
    • Lee, G.1    Han, C.2    Yoon, E.S.3
  • 12
    • 84859698661 scopus 로고    scopus 로고
    • A PLS-based statistical approach for fault detection and isolation of robotic manipulators
    • Aug
    • R. Muradore and P. Fiorini, "A PLS-based statistical approach for fault detection and isolation of robotic manipulators," IEEE Trans. Ind. Electron., vol. 59, no. 8, pp. 3167-3175, Aug. 2012.
    • (2012) IEEE Trans. Ind. Electron. , vol.59 , Issue.8 , pp. 3167-3175
    • Muradore, R.1    Fiorini, P.2
  • 13
    • 76849100172 scopus 로고    scopus 로고
    • Decentralized fault diagnosis of large-scale processes using multiblock kernel partial least squares
    • Feb
    • Y. Zhang, H. Zhou, S. J. Qin, and T. Chai, "Decentralized fault diagnosis of large-scale processes using multiblock kernel partial least squares," IEEE Trans. Ind. Informat., vol. 6, no. 1, pp. 3-10, Feb. 2010.
    • (2010) IEEE Trans. Ind. Informat. , vol.6 , Issue.1 , pp. 3-10
    • Zhang, Y.1    Zhou, H.2    Qin, S.J.3    Chai, T.4
  • 14
    • 76549132623 scopus 로고    scopus 로고
    • Complex process quality prediction using modified kernel partial least squares
    • Mar
    • Y. Zhang, Y. Teng, and Y. Zhang, "Complex process quality prediction using modified kernel partial least squares," Chem. Eng. Sci., vol. 65, no. 6, pp. 2153-2158, Mar. 2010.
    • (2010) Chem. Eng. Sci. , vol.65 , Issue.6 , pp. 2153-2158
    • Zhang, Y.1    Teng, Y.2    Zhang, Y.3
  • 15
    • 79961136607 scopus 로고    scopus 로고
    • A survey on iterative learning control for nonlinear systems
    • J.-X. Xu, "A survey on iterative learning control for nonlinear systems," Int. J. Control, vol. 84, no. 7, pp. 1275-1294, 2011.
    • (2011) Int. J. Control , vol.84 , Issue.7 , pp. 1275-1294
    • Xu, J.-X.1
  • 16
    • 71849101609 scopus 로고    scopus 로고
    • Survey on iterative learning control, repetitive control, run-to-run control
    • Dec
    • Y.Wang, F. Gao, and F. J. Doyle, III, "Survey on iterative learning control, repetitive control, run-to-run control," J. Process Control, vol. 19, no. 10, pp. 1589-1600, Dec. 2009.
    • (2009) J. Process Control , vol.19 , Issue.10 , pp. 1589-1600
    • Wang, Y.1    Gao, F.2    Doyle, F.J.3
  • 17
    • 84875920126 scopus 로고    scopus 로고
    • From model-based control to data-driven control: Survey, classification and perspective
    • Jun
    • Z. Hou and Z. Wang, "From model-based control to data-driven control: Survey, classification and perspective," Inf. Sci., vol. 235, pp. 3-35, Jun. 2013.
    • (2013) Inf. Sci. , vol.235 , pp. 3-35
    • Hou, Z.1    Wang, Z.2
  • 18
    • 80052872864 scopus 로고    scopus 로고
    • A novel data-driven control approach for a class of discrete-time nonlinear systems
    • Nov
    • Z. Hou and S. Jin, "A novel data-driven control approach for a class of discrete-time nonlinear systems," IEEE Trans. Control Syst. Technol., vol. 19, no. 6, pp. 1549-1558, Nov. 2011.
    • (2011) IEEE Trans. Control Syst. Technol. , vol.19 , Issue.6 , pp. 1549-1558
    • Hou, Z.1    Jin, S.2
  • 19
    • 83655192094 scopus 로고    scopus 로고
    • Data-driven model-free adaptive control for a class of MIMO nonlinear discrete-time systems
    • Dec
    • Z. Hou and S. Jin, "Data-driven model-free adaptive control for a class of MIMO nonlinear discrete-time systems," IEEE Trans. Neural Netw., vol. 22, no. 12, pp. 2173-2188, Dec. 2011.
    • (2011) IEEE Trans. Neural Netw. , vol.22 , Issue.12 , pp. 2173-2188
    • Hou, Z.1    Jin, S.2
  • 20
    • 72149132838 scopus 로고    scopus 로고
    • Subspace method aided data-driven design of fault detection and isolation systems
    • Oct
    • S. X. Ding, P. Zhang, A. Naik, E. Ding, and B. Huang, "Subspace method aided data-driven design of fault detection and isolation systems," J. Process Control, vol. 19, no. 9, pp. 1496-1510, Oct. 2009.
    • (2009) J. Process Control , vol.19 , Issue.9 , pp. 1496-1510
    • Ding, S.X.1    Zhang, P.2    Naik, A.3    Ding, E.4    Huang, B.5
  • 21
    • 80053624122 scopus 로고    scopus 로고
    • Subspace aided data-driven design of robust fault detection and isolation systems
    • Nov
    • Y. Wang, G. Ma, S. X. Ding, and C. Li, "Subspace aided data-driven design of robust fault detection and isolation systems," Automatica, vol. 47, no. 11, pp. 2474-2480, Nov. 2011.
    • (2011) Automatica , vol.47 , Issue.11 , pp. 2474-2480
    • Wang, Y.1    Ma, G.2    Ding, S.X.3    Li, C.4
  • 22
    • 63249126041 scopus 로고    scopus 로고
    • Improving convergence of iterative feedback tuning
    • Apr
    • J. K. Huusom, N. K. Poulsen, and S. B. Jørgensen, "Improving convergence of iterative feedback tuning," J. Process Control, vol. 19, no. 4, pp. 570-578, Apr. 2009.
    • (2009) J. Process Control , vol.19 , Issue.4 , pp. 570-578
    • Huusom, J.K.1    Poulsen, N.K.2    Jørgensen, S.B.3
  • 23
    • 31444450515 scopus 로고    scopus 로고
    • Direct nonlinear control design: The virtual reference feedback tuning VRFT approach
    • Jan
    • M. C. Campi and S. M. Savaresi, "Direct nonlinear control design: The virtual reference feedback tuning VRFT approach," IEEE Trans. Automat. Control, vol. 51, no. 1, pp. 14-27, Jan. 2006.
    • (2006) IEEE Trans. Automat. Control , vol.51 , Issue.1 , pp. 14-27
    • Campi, M.C.1    Savaresi, S.M.2
  • 24
    • 73049084841 scopus 로고    scopus 로고
    • Geometric properties of partial least squares for process monitoring
    • Jan
    • G. Li, S. J. Qin, and D. Zhou, "Geometric properties of partial least squares for process monitoring," Automatica, vol. 46, no. 1, pp. 204-210, Jan. 2010.
    • (2010) Automatica , vol.46 , Issue.1 , pp. 204-210
    • Li, G.1    Qin, S.J.2    Zhou, D.3
  • 25
    • 79955839741 scopus 로고    scopus 로고
    • Robust data-driven modeling approach for real-time final product quality prediction in batch process operation
    • May
    • D. Wang, "Robust data-driven modeling approach for real-time final product quality prediction in batch process operation," IEEE Trans. Ind. Informat., vol. 7, no. 2, pp. 371-377, May 2011.
    • (2011) IEEE Trans. Ind. Informat. , vol.7 , Issue.2 , pp. 371-377
    • Wang, D.1
  • 26
    • 84859709514 scopus 로고    scopus 로고
    • A TS fuzzy system learned through a support vector machine in principal component space for real-time object detection
    • Aug
    • C.-F. Juang and G.-C. Chen, "A TS fuzzy system learned through a support vector machine in principal component space for real-time object detection," IEEE Trans. Ind. Electron., vol. 59, no. 8, pp. 3309-3320, Aug. 2012.
    • (2012) IEEE Trans. Ind. Electron. , vol.59 , Issue.8 , pp. 3309-3320
    • Juang, C.-F.1    Chen, G.-C.2
  • 27
    • 65549141296 scopus 로고    scopus 로고
    • Principal component imagery for the quality monitoring of dynamic laser welding processes
    • Apr
    • M. Jager and F. A. Hamprecht, "Principal component imagery for the quality monitoring of dynamic laser welding processes," IEEE Trans. Ind. Electron., vol. 56, no. 4, pp. 1307-1313, Apr. 2009.
    • (2009) IEEE Trans. Ind. Electron. , vol.56 , Issue.4 , pp. 1307-1313
    • Jager, M.1    Hamprecht, F.A.2
  • 28
    • 80455156374 scopus 로고    scopus 로고
    • Diagnosis of three-phase electrical machines using multidimensional demodulation techniques
    • Apr
    • V. Choqueuse, M. E. H. Benbouzid, Y. Amirat, and S. Turri, "Diagnosis of three-phase electrical machines using multidimensional demodulation techniques," IEEE Trans. Ind. Electron., vol. 59, no. 4, pp. 2014-2023, Apr. 2012.
    • (2012) IEEE Trans. Ind. Electron. , vol.59 , Issue.4 , pp. 2014-2023
    • Choqueuse, V.1    Benbouzid, M.E.H.2    Amirat, Y.3    Turri, S.4
  • 29
    • 84863014249 scopus 로고    scopus 로고
    • Local and nonlocal preserving projection for bearing defect classification and performance assessment
    • May 2012
    • J. Yu, "Local and nonlocal preserving projection for bearing defect classification and performance assessment," IEEE Trans. Ind. Electron., vol. 59, no. 5, pp. 2363-2376, May 2012.
    • IEEE Trans. Ind. Electron. , vol.59 , Issue.5 , pp. 2363-2376
    • Yu, J.1
  • 30
    • 79954497424 scopus 로고    scopus 로고
    • A simple real-time fault signature monitoring tool for motor-drive-embedded fault diagnosis systems
    • May
    • B. Akin, S. Choi, U. Orguner, and H. A. Toliyat, "A simple real-time fault signature monitoring tool for motor-drive-embedded fault diagnosis systems," IEEE Trans. Ind. Electron., vol. 58, no. 5, pp. 1990-2001, May 2011.
    • (2011) IEEE Trans. Ind. Electron. , vol.58 , Issue.5 , pp. 1990-2001
    • Akin, B.1    Choi, S.2    Orguner, U.3    Toliyat, H.A.4
  • 31
    • 84863009414 scopus 로고    scopus 로고
    • Fault diagnosis and fault-tolerant control in linear drives using the Kalman filter
    • Nov
    • S. Huang, K. K. Tan, and T. H. Lee, "Fault diagnosis and fault-tolerant control in linear drives using the Kalman filter," IEEE Trans. Ind. Electron., vol. 59, no. 11, pp. 4285-4292, Nov. 2012.
    • (2012) IEEE Trans. Ind. Electron. , vol.59 , Issue.11 , pp. 4285-4292
    • Huang, S.1    Tan, K.K.2    Lee, T.H.3
  • 32
    • 84876224648 scopus 로고    scopus 로고
    • Plastic bearing fault diagnosis based on a twostep data mining approach
    • Aug
    • D. He, R. Li, and J. Zhu, "Plastic bearing fault diagnosis based on a twostep data mining approach," IEEE Trans. Ind. Electron., vol. 60, no. 8, pp. 3429-3440, Aug. 2013.
    • (2013) IEEE Trans. Ind. Electron. , vol.60 , Issue.8 , pp. 3429-3440
    • He, D.1    Li, R.2    Zhu, J.3
  • 34
    • 77951090351 scopus 로고    scopus 로고
    • On-line batch process monitoring using batch dynamic kernel principal component analysis
    • Apr
    • M. Jia, F. Chu, F.Wang, andW.Wang, "On-line batch process monitoring using batch dynamic kernel principal component analysis," Chemometr. Intell. Lab., vol. 101, no. 2, pp. 110-122, Apr. 2010.
    • (2010) Chemometr. Intell. Lab. , vol.101 , Issue.2 , pp. 110-122
    • Jia, M.1    Chu, F.2    Wang, F.3    Wang, W.4
  • 35
    • 77955274753 scopus 로고    scopus 로고
    • Integrating independent component analysis and support vector machine for multivariate process monitoring
    • Aug
    • C.-C. Hsu,M.-C. Chen, and L.-S. Chen, "Integrating independent component analysis and support vector machine for multivariate process monitoring," Comput. Ind. Eng., vol. 59, no. 1, pp. 145-156, Aug. 2010.
    • (2010) Comput. Ind. Eng. , vol.59 , Issue.1 , pp. 145-156
    • Hsu, C.-C.1    Chen, M.-C.2    Chen, L.-S.3
  • 36
    • 84883765694 scopus 로고    scopus 로고
    • Fault diagnosis for power system transmission line based on PCA and SVMs
    • Y. Guo, K. Li, and X. Liu, "Fault diagnosis for power system transmission line based on PCA and SVMs," in Proc. ICSEE, 2013, pp. 524-532.
    • (2013) Proc. ICSEE , pp. 524-532
    • Guo, Y.1    Li, K.2    Liu, X.3
  • 37
    • 65549154885 scopus 로고    scopus 로고
    • Variable-weighted Fisher discriminant analysis for process fault diagnosis
    • Jun
    • X. B. He,W.Wang, Y. P. Yang, and Y. H. Yang, "Variable-weighted Fisher discriminant analysis for process fault diagnosis," J. Process Control, vol. 19, no. 6, pp. 923-931, Jun. 2009.
    • (2009) J. Process Control , vol.19 , Issue.6 , pp. 923-931
    • He, X.B.1    Wang, W.2    Yang, Y.P.3    Yang, Y.H.4
  • 38
    • 79958703777 scopus 로고    scopus 로고
    • Localized Fisher discriminant analysis based complex chemical process monitoring
    • Jul
    • J. Yu, "Localized Fisher discriminant analysis based complex chemical process monitoring," AIChE J., vol. 57, no. 7, pp. 1817-1828, Jul. 2011.
    • (2011) AIChE J. , vol.57 , Issue.7 , pp. 1817-1828
    • Yu, J.1
  • 39
    • 79952591121 scopus 로고    scopus 로고
    • Nonlinear bioprocess monitoring using multiway kernel localized Fisher discriminant analysis
    • J. Yu, "Nonlinear bioprocess monitoring using multiway kernel localized Fisher discriminant analysis," Ind. Eng. Chem. Res., vol. 50, no. 6, pp. 3390-3402, 2011.
    • (2011) Ind. Eng. Chem. Res. , vol.50 , Issue.6 , pp. 3390-3402
    • Yu, J.1
  • 40
    • 56349114104 scopus 로고    scopus 로고
    • Improved kernel Fisher discriminant analysis for fault diagnosis
    • Mar
    • J. Li and P. Cui, "Improved kernel Fisher discriminant analysis for fault diagnosis," Expert Syst. Appl., vol. 36, no. 2, pp. 1423-1432, Mar. 2009.
    • (2009) Expert Syst. Appl. , vol.36 , Issue.2 , pp. 1423-1432
    • Li, J.1    Cui, P.2
  • 41
    • 71349084565 scopus 로고    scopus 로고
    • Intelligent ICA-SVM fault detector for non-Gaussian multivariate process monitoring
    • Apr
    • C.-C. Hsu, M.-C. Chen, and L.-S. Chen, "Intelligent ICA-SVM fault detector for non-Gaussian multivariate process monitoring," Expert Syst. Appl., vol. 37, no. 4, pp. 3264-3273, Apr. 2010.
    • (2010) Expert Syst. Appl. , vol.37 , Issue.4 , pp. 3264-3273
    • Hsu, C.-C.1    Chen, M.-C.2    Chen, L.-S.3
  • 42
    • 77954386508 scopus 로고    scopus 로고
    • Fault detection of non-Gaussian processes based on modified independent component analysis
    • Aug
    • Y. Zhang and Y. Zhang, "Fault detection of non-Gaussian processes based on modified independent component analysis," Chem. Eng. Sci., vol. 65, no. 16, pp. 4630-4639, Aug. 2010.
    • (2010) Chem. Eng. Sci. , vol.65 , Issue.16 , pp. 4630-4639
    • Zhang, Y.1    Zhang, Y.2
  • 43
    • 84870160474 scopus 로고    scopus 로고
    • Data-driven adaptive observer for fault diagnosis
    • S. Yin, X. Yang, and H. R. Karimi, "Data-driven adaptive observer for fault diagnosis," Math. Probl. Eng., vol. 2012, pp. 832836-1-832836-21, 2012.
    • (2012) Math. Probl. Eng. , vol.2012 , pp. 8328361-83283621
    • Yin, S.1    Yang, X.2    Karimi, H.R.3
  • 44
    • 77955513371 scopus 로고    scopus 로고
    • Recursive identification algorithms to design fault detection systems
    • Sep
    • A. S. Naik, S. Yin, S. X. Ding, and P. Zhang, "Recursive identification algorithms to design fault detection systems," J. Process Control, vol. 20, no. 8, pp. 957-965, Sep. 2010.
    • (2010) J. Process Control , vol.20 , Issue.8 , pp. 957-965
    • Naik, A.S.1    Yin, S.2    Ding, S.X.3    Zhang, P.4
  • 45
    • 77649188417 scopus 로고    scopus 로고
    • Feedback control structures, embedded residual signals, feedback control schemes with an integrated residual access
    • Mar
    • S. X. Ding, G. Yang, P. Zhang, E. Ding, T. Jeinsch, N. Weinhold, and M. Schultalbers, "Feedback control structures, embedded residual signals, feedback control schemes with an integrated residual access," IEEE Trans. Control Syst. Technol., vol. 18, no. 2, pp. 352-367, Mar. 2010.
    • (2010) IEEE Trans. Control Syst. Technol. , vol.18 , Issue.2 , pp. 352-367
    • Ding, S.X.1    Yang, G.2    Zhang, P.3    Ding, E.4    Jeinsch, T.5    Weinhold, N.6    Schultalbers, M.7
  • 47
    • 84860674158 scopus 로고    scopus 로고
    • An approach to data-driven design of feedback control systems with embedded residual generation
    • S. X. Ding, Y. Wang, and Y. Yang, "An approach to data-driven design of feedback control systems with embedded residual generation," in Proc. 50th IEEE CDC-ECC, 2011, pp. 885-890.
    • (2011) Proc. 50th IEEE CDC-ECC , pp. 885-890
    • Ding, S.X.1    Wang, Y.2    Yang, Y.3
  • 48
    • 79954455895 scopus 로고    scopus 로고
    • Cascade neural-network-based fault classifier for three-phase induction motor
    • May
    • V. N. Ghate and S. V. Dudul, "Cascade neural-network-based fault classifier for three-phase induction motor," IEEE Trans. Ind. Electron., vol. 58, no. 5, pp. 1555-1563, May 2011.
    • (2011) IEEE Trans. Ind. Electron. , vol.58 , Issue.5 , pp. 1555-1563
    • Ghate, V.N.1    Dudul, S.V.2
  • 49
    • 77950593813 scopus 로고    scopus 로고
    • Simultaneous process mean and variance monitoring using artificial neural networks
    • May
    • R.-S. Guh, "Simultaneous process mean and variance monitoring using artificial neural networks," Comput. Ind. Eng., vol. 58, no. 4, pp. 739-753, May 2010.
    • (2010) Comput. Ind. Eng. , vol.58 , Issue.4 , pp. 739-753
    • Guh, R.-S.1
  • 50
    • 79951618543 scopus 로고    scopus 로고
    • Implementation of a fault-diagnosis algorithm for induction machines based on advanced digital-signal-processing techniques
    • Mar
    • S. Choi, B. Akin, M. M. Rahimian, and H. A. Toliyat, "Implementation of a fault-diagnosis algorithm for induction machines based on advanced digital-signal-processing techniques," IEEE Trans. Ind. Electron., vol. 58, no. 3, pp. 937-948, Mar. 2011.
    • (2011) IEEE Trans. Ind. Electron. , vol.58 , Issue.3 , pp. 937-948
    • Choi, S.1    Akin, B.2    Rahimian, M.M.3    Toliyat, H.A.4
  • 51
    • 40449094552 scopus 로고    scopus 로고
    • From large chemical plant data to fault diagnosis integrated to decentralized fault-tolerant control: Pulp mill process application
    • D. Zumoffen and M. Basualdo, "From large chemical plant data to fault diagnosis integrated to decentralized fault-tolerant control: Pulp mill process application," Ind. Eng. Chem. Res., vol. 47, no. 4, pp. 1201-1220, 2008.
    • (2008) Ind. Eng. Chem. Res. , vol.47 , Issue.4 , pp. 1201-1220
    • Zumoffen, D.1    Basualdo, M.2
  • 52
    • 43449112408 scopus 로고    scopus 로고
    • A data-driven H2-optimal control approach for adaptive optics
    • May
    • K. Hinnen, M. Verhaegen, and N. Doelman, "A data-driven H2-optimal control approach for adaptive optics," IEEE Trans. Control Syst. Technol., vol. 16, no. 3, pp. 381-395, May 2008.
    • (2008) IEEE Trans. Control Syst. Technol. , vol.16 , Issue.3 , pp. 381-395
    • Hinnen, K.1    Verhaegen, M.2    Doelman, N.3
  • 53
    • 79955583182 scopus 로고    scopus 로고
    • Data-driven adaptive model-based predictive control with application in wastewater systems
    • Apr
    • N. A. Wahab, R. Katebi, J. Balderud, and M. Rahmat, "Data-driven adaptive model-based predictive control with application in wastewater systems," IET Control Theory Appl., vol. 5, no. 6, pp. 803-812, Apr. 2011.
    • (2011) IET Control Theory Appl. , vol.5 , Issue.6 , pp. 803-812
    • Wahab, N.A.1    Katebi, R.2    Balderud, J.3    Rahmat, M.4
  • 54
    • 83655201117 scopus 로고    scopus 로고
    • Data-based virtual unmodeled dynamics driven multivariable nonlinear adaptive switching control
    • Dec
    • T. Chai, Y. Zhang, H. Wang, C.-Y. Su, and J. Sun, "Data-based virtual unmodeled dynamics driven multivariable nonlinear adaptive switching control," IEEE Trans. Neural Netw., vol. 22, no. 12, pp. 2154-2172, Dec. 2011.
    • (2011) IEEE Trans. Neural Netw. , vol.22 , Issue.12 , pp. 2154-2172
    • Chai, T.1    Zhang, Y.2    Wang, H.3    Su, C.-Y.4    Sun, J.5
  • 55
    • 83655163786 scopus 로고    scopus 로고
    • Data-driven robust approximate optimal tracking control for unknown general nonlinear systems using adaptive dynamic programming method
    • Dec
    • H. Zhang, L. Cui, X. Zhang, and Y. Luo, "Data-driven robust approximate optimal tracking control for unknown general nonlinear systems using adaptive dynamic programming method," IEEE Trans. Neural Netw., vol. 22, no. 12, pp. 2226-2236, Dec. 2011.
    • (2011) IEEE Trans. Neural Netw. , vol.22 , Issue.12 , pp. 2226-2236
    • Zhang, H.1    Cui, L.2    Zhang, X.3    Luo, Y.4
  • 56
    • 84878577457 scopus 로고    scopus 로고
    • Discrete non-linear adaptive data driven control based upon simultaneous perturbation stochastic approximation
    • Jun
    • N. Dong, A. Wu, and Z. Chen, "Discrete non-linear adaptive data driven control based upon simultaneous perturbation stochastic approximation," Nonlinear Dyn., vol. 72, pp. 883-894, Jun. 2013.
    • (2013) Nonlinear Dyn. , vol.72 , pp. 883-894
    • Dong, N.1    Wu, A.2    Chen, Z.3
  • 57
    • 78149280441 scopus 로고    scopus 로고
    • Data-driven latent-variable model-based predictive control for continuous processes
    • Dec
    • D. Laurí, J. Rossiter, J. Sanchis, and M. Martínez, "Data-driven latent-variable model-based predictive control for continuous processes," J. Process Control, vol. 20, no. 10, pp. 1207-1219, Dec. 2010.
    • (2010) J. Process Control , vol.20 , Issue.10 , pp. 1207-1219
    • Laurí, D.1    Rossiter, J.2    Sanchis, J.3    Martínez, M.4
  • 58
    • 80052566590 scopus 로고    scopus 로고
    • Sensitivity compensating control: Data-driven model based adaptive approach
    • Oct
    • K. Y. Rani, "Sensitivity compensating control: Data-driven model based adaptive approach," J. Process Control, vol. 21, no. 9, pp. 1265-1286, Oct. 2011.
    • (2011) J. Process Control , vol.21 , Issue.9 , pp. 1265-1286
    • Rani, K.Y.1
  • 59
    • 84859896649 scopus 로고    scopus 로고
    • Data driven adaptive predictive control for holonomic constrained under-actuated biped robots
    • May
    • S. S. Ge, Z. Li, and H. Yang, "Data driven adaptive predictive control for holonomic constrained under-actuated biped robots," IEEE Trans. Control Syst. Technol., vol. 20, no. 3, pp. 787-795, May 2012.
    • (2012) IEEE Trans. Control Syst. Technol. , vol.20 , Issue.3 , pp. 787-795
    • Ge, S.S.1    Li, Z.2    Yang, H.3
  • 60
    • 36348994389 scopus 로고    scopus 로고
    • Iterative learning control: Brief survey and categorization
    • Nov
    • H.-S. Ahn, Y. Chen, and K. L. Moore, "Iterative learning control: Brief survey and categorization," IEEE Trans. Syst., Man, Cybern. C, Appl. Rev., vol. 37, no. 6, pp. 1099-1121, Nov. 2007.
    • (2007) IEEE Trans. Syst., Man, Cybern. C, Appl. Rev. , vol.37 , Issue.6 , pp. 1099-1121
    • Ahn, H.-S.1    Chen, Y.2    Moore, K.L.3
  • 61
    • 83655184652 scopus 로고    scopus 로고
    • Data-driven control for relative degree systems via iterative learning
    • Dec
    • D. Meng, Y. Jia, J. Du, and F. Yu, "Data-driven control for relative degree systems via iterative learning," IEEE Trans. Neural Netw., vol. 22, no. 12, pp. 2213-2225, Dec. 2011.
    • (2011) IEEE Trans. Neural Netw. , vol.22 , Issue.12 , pp. 2213-2225
    • Meng, D.1    Jia, Y.2    Du, J.3    Yu, F.4
  • 62
    • 84870463544 scopus 로고    scopus 로고
    • Data-driven optimal terminal iterative learning control
    • Dec
    • R. Chi, D. Wang, Z. Hou, and S. Jin, "Data-driven optimal terminal iterative learning control," J. Process Control, vol. 22, no. 10, pp. 2026-2037, Dec. 2012.
    • (2012) J. Process Control , vol.22 , Issue.10 , pp. 2026-2037
    • Chi, R.1    Wang, D.2    Hou, Z.3    Jin, S.4
  • 63
    • 84874660637 scopus 로고    scopus 로고
    • A data-driven constrained norm-optimal iterative learning control framework for LTI systems
    • Mar
    • P. Janssens, G. Pipeleers, and J. Swevers, "A data-driven constrained norm-optimal iterative learning control framework for LTI systems," IEEE Trans. Control Syst. Technol., vol. 21, no. 2, pp. 546-551, Mar. 2013.
    • (2013) IEEE Trans. Control Syst. Technol. , vol.21 , Issue.2 , pp. 546-551
    • Janssens, P.1    Pipeleers, G.2    Swevers, J.3
  • 64
    • 84865248109 scopus 로고    scopus 로고
    • Local models for data-driven learning of control policies for complex systems
    • Dec
    • D. Macciò and C. Cervellera, "Local models for data-driven learning of control policies for complex systems," Expert Syst. Appl., vol. 39, no. 18, pp. 13 399-13 408, Dec. 2012.
    • (2012) Expert Syst. Appl. , vol.39 , Issue.18 , pp. 13399-13408
    • Macciò, D.1    Cervellera, C.2
  • 65
    • 67349210675 scopus 로고    scopus 로고
    • Application of iterative feedback tuning (IFT) to speed and position control of a servo drive
    • Jul
    • S. Kissling, P. Blanc, P. Myszkorowski, and I. Vaclavik, "Application of iterative feedback tuning (IFT) to speed and position control of a servo drive," Control Eng. Pract., vol. 17, no. 7, pp. 834-840, Jul. 2009.
    • (2009) Control Eng. Pract. , vol.17 , Issue.7 , pp. 834-840
    • Kissling, S.1    Blanc, P.2    Myszkorowski, P.3    Vaclavik, I.4
  • 66
    • 73249142318 scopus 로고    scopus 로고
    • Iterative tuning of internal model controllers with application to air/fuel ratio control
    • Jan
    • D. Rupp and L. Guzzella, "Iterative tuning of internal model controllers with application to air/fuel ratio control," IEEE Trans. Control Syst. Technol., vol. 18, no. 1, pp. 177-184, Jan. 2010.
    • (2010) IEEE Trans. Control Syst. Technol. , vol.18 , Issue.1 , pp. 177-184
    • Rupp, D.1    Guzzella, L.2
  • 67
    • 79960928016 scopus 로고    scopus 로고
    • Virtual reference feedback tuning for non-minimum phase plants
    • Aug
    • L. Campestrini, D. Eckhard, M. Gevers, and A. S. Bazanella, "Virtual reference feedback tuning for non-minimum phase plants," Automatica, vol. 47, no. 8, pp. 1778-1784, Aug. 2011.
    • (2011) Automatica , vol.47 , Issue.8 , pp. 1778-1784
    • Campestrini, L.1    Eckhard, D.2    Gevers, M.3    Bazanella, A.S.4
  • 68
    • 70049104692 scopus 로고    scopus 로고
    • Anticipatory control of wind turbines with data-driven predictive models
    • Sep
    • A. Kusiak, Z. Song, and H. Zheng, "Anticipatory control of wind turbines with data-driven predictive models," IEEE Trans. Energy Convers., vol. 24, no. 3, pp. 766-774, Sep. 2009.
    • (2009) IEEE Trans. Energy Convers. , vol.24 , Issue.3 , pp. 766-774
    • Kusiak, A.1    Song, Z.2    Zheng, H.3
  • 69
    • 84870449520 scopus 로고    scopus 로고
    • Automatic controller tuning via unfalsified control
    • Dec
    • T. Wonghong and S. Engell, "Automatic controller tuning via unfalsified control," J. Process Control, vol. 22, no. 10, pp. 2008-2025, Dec. 2012.
    • (2012) J. Process Control , vol.22 , Issue.10 , pp. 2008-2025
    • Wonghong, T.1    Engell, S.2
  • 70
    • 84862864158 scopus 로고    scopus 로고
    • Passivity criteria for continuous-time neural networks with mixed time-varying delays
    • Jul
    • H. Li, J. Lam, and K. Cheung, "Passivity criteria for continuous-time neural networks with mixed time-varying delays," Appl. Math. Comput., vol. 218, no. 22, pp. 11 062-11 074, Jul. 2012.
    • (2012) Appl. Math. Comput. , vol.218 , Issue.22 , pp. 11062-11074
    • Li, H.1    Lam, J.2    Cheung, K.3
  • 71
    • 79956290240 scopus 로고    scopus 로고
    • A loss inference algorithm for wireless sensor networks to improve data reliability of digital ecosystems
    • Jun
    • Y. Yang, Y. Xu, X. Li, and C. Chen, "A loss inference algorithm for wireless sensor networks to improve data reliability of digital ecosystems," IEEE Trans. Ind. Electron., vol. 58, no. 6, pp. 2126-2137, Jun. 2011.
    • (2011) IEEE Trans. Ind. Electron. , vol.58 , Issue.6 , pp. 2126-2137
    • Yang, Y.1    Xu, Y.2    Li, X.3    Chen, C.4
  • 72
    • 79954529650 scopus 로고    scopus 로고
    • Distributed H8 filtering for polynomial nonlinear stochastic systems in sensor networks
    • May
    • B. Shen, Z. Wang, Y. Hung, and G. Chesi, "Distributed H8 filtering for polynomial nonlinear stochastic systems in sensor networks," IEEE Trans. Ind. Electron., vol. 58, no. 5, pp. 1971-1979, May 2011.
    • (2011) IEEE Trans. Ind. Electron. , vol.58 , Issue.5 , pp. 1971-1979
    • Shen, B.1    Wang, Z.2    Hung, Y.3    Chesi, G.4
  • 73
    • 84878121569 scopus 로고    scopus 로고
    • Distributed H8 filtering for a class of Markovian jump nonlinear time-delay systems over lossy sensor networks
    • Oct
    • H. Dong, Z. Wang, and H. Gao, "Distributed H8 filtering for a class of Markovian jump nonlinear time-delay systems over lossy sensor networks," IEEE Trans. Ind. Electron., vol. 60, no. 10, pp. 4665-4672, Oct. 2013.
    • (2013) IEEE Trans. Ind. Electron. , vol.60 , Issue.10 , pp. 4665-4672
    • Dong, H.1    Wang, Z.2    Gao, H.3
  • 74
    • 26844444153 scopus 로고    scopus 로고
    • Adaptive power control for wireless networks using multiple controllers and switching
    • Sep
    • A. Paul, M. Akar, M. G. Safonov, and U. Mitra, "Adaptive power control for wireless networks using multiple controllers and switching," IEEE Trans. Neural Netw., vol. 16, no. 5, pp. 1212-1218, Sep. 2005.
    • (2005) IEEE Trans. Neural Netw. , vol.16 , Issue.5 , pp. 1212-1218
    • Paul, A.1    Akar, M.2    Safonov, M.G.3    Mitra, U.4
  • 75
    • 41149098596 scopus 로고    scopus 로고
    • Nonlinear model predictive control for distributed parameter systems using data driven artificial neural network models
    • Jun
    • E. Aggelogiannaki and H. Sarimveis, "Nonlinear model predictive control for distributed parameter systems using data driven artificial neural network models," Comput. Chem. Eng., vol. 32, no. 6, pp. 1225-1237, Jun. 2008.
    • (2008) Comput. Chem. Eng. , vol.32 , Issue.6 , pp. 1225-1237
    • Aggelogiannaki, E.1    Sarimveis, H.2
  • 76
    • 84859741306 scopus 로고    scopus 로고
    • Data-driven communication for state estimation with sensor networks
    • May
    • G. Battistelli, A. Benavoli, and L. Chisci, "Data-driven communication for state estimation with sensor networks," Automatica, vol. 48, no. 5, pp. 926-935, May 2012.
    • (2012) Automatica , vol.48 , Issue.5 , pp. 926-935
    • Battistelli, G.1    Benavoli, A.2    Chisci, L.3
  • 77
    • 84875962362 scopus 로고    scopus 로고
    • Data-driven predictive control for networked control systems
    • Jun
    • Y. Xia, W. Xie, B. Liu, and X. Wang, "Data-driven predictive control for networked control systems," Inf. Sci., vol. 235, pp. 45-54, Jun. 2013.
    • (2013) Inf. Sci. , vol.235 , pp. 45-54
    • Xia, Y.1    Xie, W.2    Liu, B.3    Wang, X.4
  • 78
    • 79251627926 scopus 로고    scopus 로고
    • Stability of networked control system with dynamic quantizer and data-driven zero-order hold
    • Feb
    • E. Konaka, "Stability of networked control system with dynamic quantizer and data-driven zero-order hold," Electron. Commun. Jpn., vol. 94, no. 2, pp. 1-8, Feb. 2011.
    • (2011) Electron. Commun. Jpn. , vol.94 , Issue.2 , pp. 1-8
    • Konaka, E.1
  • 79
    • 84890754450 scopus 로고    scopus 로고
    • Cloud computing for industrial automation systems-A comprehensive overview
    • IEEE
    • O. Givehchi, H. Trsek, and J. Jasperneite, "Cloud computing for industrial automation systems-A comprehensive overview," in Proc. 18th IEEE ETFA, 2013, pp. 1-4, IEEE.
    • (2013) Proc. 18th IEEE ETFA , pp. 1-4
    • Givehchi, O.1    Trsek, H.2    Jasperneite, J.3
  • 80
    • 78650332092 scopus 로고    scopus 로고
    • A data-driven approach for monitoring blade pitch faults in wind turbines
    • Jan
    • A. Kusiak and A. Verma, "A data-driven approach for monitoring blade pitch faults in wind turbines," IEEE Trans. Sustainable Energy, vol. 2, no. 1, pp. 87-96, Jan. 2011.
    • (2011) IEEE Trans. Sustainable Energy , vol.2 , Issue.1 , pp. 87-96
    • Kusiak, A.1    Verma, A.2
  • 81
    • 84862213461 scopus 로고    scopus 로고
    • Monitoring of wind farms' power curves using machine learning techniques
    • Oct
    • A. Marvuglia and A.Messineo, "Monitoring of wind farms' power curves using machine learning techniques," Appl. Energ., vol. 98, pp. 574-583, Oct. 2012.
    • (2012) Appl. Energ. , vol.98 , pp. 574-583
    • Marvuglia, A.1    Messineo, A.2
  • 82
    • 84873724101 scopus 로고    scopus 로고
    • Global data-driven modeling of wind turbines in the presence of turbulence
    • Apr
    • G. van der Veen, J. van Wingerden, P. Fleming, A. Scholbrock, and M. Verhaegen, "Global data-driven modeling of wind turbines in the presence of turbulence," Control Eng. Pract., vol. 21, no. 4, pp. 441-454, Apr. 2013.
    • (2013) Control Eng. Pract. , vol.21 , Issue.4 , pp. 441-454
    • Veen Der G.Van1    Van Wingerden, J.2    Fleming, P.3    Scholbrock, A.4    Verhaegen, M.5
  • 83
    • 85008043357 scopus 로고    scopus 로고
    • Power quality disturbance classification using fuzzy C-means algorithm and adaptive particle swarm optimization
    • Jan
    • B. Biswal, P. K. Dash, and B. K. Panigrahi, "Power quality disturbance classification using fuzzy C-means algorithm and adaptive particle swarm optimization," IEEE Trans. Ind. Electron., vol. 56, no. 1, pp. 212-220, Jan. 2009.
    • (2009) IEEE Trans. Ind. Electron. , vol.56 , Issue.1 , pp. 212-220
    • Biswal, B.1    Dash, P.K.2    Panigrahi, B.K.3
  • 84
    • 80051711986 scopus 로고    scopus 로고
    • Fault diagnosis in industrial induction machines through discrete wavelet transform
    • Sep
    • A. Bouzida, O. Touhami, R. Ibtiouen, A. Belouchrani, M. Fadel, and A. Rezzoug, "Fault diagnosis in industrial induction machines through discrete wavelet transform," IEEE Trans. Ind. Electron., vol. 58, no. 9, pp. 4385-4395, Sep. 2011.
    • (2011) IEEE Trans. Ind. Electron. , vol.58 , Issue.9 , pp. 4385-4395
    • Bouzida, A.1    Touhami, O.2    Ibtiouen, R.3    Belouchrani, A.4    Fadel, M.5    Rezzoug, A.6
  • 85
    • 70349619163 scopus 로고    scopus 로고
    • Industrial wireless sensor networks: Challenges, design principles, technical approaches
    • Oct
    • V. C. Gungor and G. P. Hancke, "Industrial wireless sensor networks: Challenges, design principles, technical approaches," IEEE Trans. Ind. Electron., vol. 56, no. 10, pp. 4258-4265, Oct. 2009.
    • (2009) IEEE Trans. Ind. Electron. , vol.56 , Issue.10 , pp. 4258-4265
    • Gungor, V.C.1    Hancke, G.P.2
  • 86
    • 77956607253 scopus 로고    scopus 로고
    • Opportunities and challenges of wireless sensor networks in smart grid
    • Oct
    • V. C. Gungor, B. Lu, and G. P. Hancke, "Opportunities and challenges of wireless sensor networks in smart grid," IEEE Trans. Ind. Electron., vol. 57, no. 10, pp. 3557-3564, Oct. 2010.
    • (2010) IEEE Trans. Ind. Electron. , vol.57 , Issue.10 , pp. 3557-3564
    • Gungor, V.C.1    Lu, B.2    Hancke, G.P.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.