과제정보
연구 과제 주관 기관 : Korea Institute of Energy Technology Evaluation and Planning (KETEP), National Research Foundation of Korea (NRF)
참고문헌
- Alavandar, S. and Nigam, M.J. (2008), "Neuro-fuzzy based approach for inverse kinematics solution of industrial robot manipulators", J. Comput. Commun. Contr., 3(3), 224-234. https://doi.org/10.15837/ijccc.2008.3.2391
- Alwi, H. and Edwards, C. (2014), "Robust fault reconstruction for linear parameter varying systems using sliding mode observers", J. Robust Nonlin. Contr., 24(14), 1947-1968. https://doi.org/10.1002/rnc.3009
- Anh, H.P.H. and Nam, N.T. (2012), "Novel adaptive forward neural MIMO NARX model for the identification of industrial 3-DOF robot arm kinematics", J. Adv. Robot. Syst., 9(4), 104. https://doi.org/10.5772/51277
- Badihi, H., Zhang, Y. and Hong, H. (2017), "Fault-tolerant cooperative control in an offshore wind farm using model-free and model-based fault detection and diagnosis approaches", Appl. Energy, 201, 284-307. https://doi.org/10.1016/j.apenergy.2016.12.096
- Bouzrara, K., Garna, T., Ragot, J. and Messaoud, H. (2013), "Online identification of the ARX model expansion on Laguerre orthonormal bases with filters on model input and output", J. Contr., 86(3), 369-385. https://doi.org/10.1080/00207179.2012.732710
- Bouzrara, K., Garna, T., Ragot, J. and Messaoud, H. (2012), "Decomposition of an ARX model on Laguerre orthonormal bases", ISA Trans., 51(6), 848-860. https://doi.org/10.1016/j.isatra.2012.06.005
- Busawon, K.K. and Kabore, P. (2001), "Disturbance attenuation using proportional integral observers", J. Contr., 74(6), 618-627. https://doi.org/10.1080/00207170010025249
- Forrai, A. (2017), "System identification and fault diagnosis of an electromagnetic actuator", IEEE T. Contr. Syst. Technol., 25(3), 1028-1035. https://doi.org/10.1109/TCST.2016.2582147
- Gao, Z., Breikin, T. and Wang, H. (2008), "Discrete-time proportional and integral observer and observerbased controller for systems with both unknown input and output disturbances", Optim. Contr. Appl. Met., 29(3), 171-189. https://doi.org/10.1002/oca.819
- Gao, Z. and Ho, D.W. (2004), "Proportional multiple-integral observer design for descriptor systems with measurement output disturbances", IEE Proc. Contr. Theor. Appl., 151(3), 279-288. https://doi.org/10.1049/ip-cta:20040437
- Gao, Z., Ding, S.X. and Ma, Y. (2007), "Robust fault estimation approach and its application in vehicle lateral dynamic systems", Optim. Contr. Appl. Met., 28(3), 143-156. https://doi.org/10.1002/oca.786
- Gao, Z. and Wang, H. (2006), "Descriptor observer approaches for multivariable systems with measurement noises and application in fault detection and diagnosis", Syst. Control Lett., 55(4), 304-313. https://doi.org/10.1016/j.sysconle.2005.08.004
- Gao, Z., Shi, X. and Ding, S.X. (2008), "Fuzzy state/disturbance observer design for T-S fuzzy systems with application to sensor fault estimation", IEEE T. Syst. Man. Cy. B, 38(3), 875-880. https://doi.org/10.1109/TSMCB.2008.917185
- Gao, Z., Dai, X., Breikin, T. and Wang, H. (2008), "Novel parameter identification by using a high-gain observer with application to a gas turbine engine", IEEE T. Ind. Inform., 4(4), 271-279. https://doi.org/10.1109/TII.2008.2007802
- Gholizadeh, M. and Salmasi, F.R. (2014), "Estimation of state of charge, unknown nonlinearities, and state of health of a lithium-ion battery based on a comprehensive unobservable model", IEEE T. Ind. Electron., 61(3), 1335-1344. https://doi.org/10.1109/TIE.2013.2259779
- Han, X., Fridman, E. and Spurgeon, S.K. (2014), "Sampled-data sliding mode observer for robust fault reconstruction: A time-delay approach", J. Franklin Inst., 351(4), 2125-2142. https://doi.org/10.1016/j.jfranklin.2013.04.004
- Hartmann, A., Lemos, J.M., Costa, R.S., Xavier, J. and Vinga, S. (2015), "Identification of switched ARX models via convex optimization and expectation maximization", J. Process Contr., 28, 9-16. https://doi.org/10.1016/j.jprocont.2015.02.003
- Jami'in, M.A., Hu, J., Marhaban, M.H., Sutrisno, I. and Mariun, N.B. (2016), "Quasi-ARX neural network based adaptive predictive control for nonlinear systems", IEEJ Trans. Elect. Electron. Eng., 11(1), 83-90. https://doi.org/10.1002/tee.22191
- Jamshidpour, E., Poure, P. and Saadate, S. (2015), "Photovoltaic systems reliability improvement by realtime FPGA-based switch failure diagnosis and fault-tolerant DC-DC converter", IEEE T. Ind. Electron., 62(11), 7247-7255. https://doi.org/10.1109/TIE.2015.2421880
- Kang, M., Kim, J. and Kim, J.M. (2015), "An FPGA-based multicore system for real-time bearing fault diagnosis using ultrasampling rate AE signals" IEEE T. Ind. Electron., 62(4), 2319-2329. https://doi.org/10.1109/TIE.2014.2361317
- Khalastchi, E., Kalech, M. and Rokach, L. (2017), "A hybrid approach for improving unsupervised fault detection for robotic systems", Expert Syst. Appl., 81, 372-383. https://doi.org/10.1016/j.eswa.2017.03.058
- Koenig, D. (2005), "Unknown input proportional multiple-integral observer design for linear descriptor systems: Application to state and fault estimation", IEEE T. Autom. Contr., 50(2), 212-217. https://doi.org/10.1109/TAC.2004.841889
- Lafont, F., Balmat, J.F., Pessel, N. and Fliess, M. (2015), "A model-free control strategy for an experimental greenhouse with an application to fault accommodation", Comput. Electron. Agr., 110, 139-149. https://doi.org/10.1016/j.compag.2014.11.008
- Lopez-Estrada, F.R., Ponsart, J.C., Theilliol, D., Zhang, Y. and Astorga-Zaragoza, C.M. (2016), "LPV model-based tracking control and robust sensor fault diagnosis for a quadrotor UAV", J. Intell. Robot. Syst., 84(1-4), 163-177. https://doi.org/10.1007/s10846-015-0295-y
- Ngoc Son, N., Anh, H.P.H. and Thanh Nam, N. (2016), "Robot manipulator identification based on adaptive multiple-input and multiple-output neural model optimized by advanced differential evolution algorithm", J. Adv. Robot. Syst., 14(1), 1729881416677695.
- Salehifar, M., Arashloo, R.S., Eguilaz, M.M. and Sala, V. (2015), "FPGA based robust open transistor fault diagnosis and fault tolerant sliding mode control of five-phase PM motor drives", J. Power Electron., 15(1), 131-145. https://doi.org/10.6113/JPE.2015.15.1.131
- Siciliano, B. and Khatib, O. (2016), Springer Handbook of Robotics, Springer.
- Simani, S., Fantuzzi, C. and Patton, R.J. (2013), Model-Based Fault Diagnosis in Dynamic Systems Using Identification Techniques, Springer Science & Business Media.
- Stavrou, D., Eliades, D.G., Panayiotou, C.G. and Polycarpou, M.M. (2016), "Fault detection for service mobile robots using model-based method", Autonom. Robot., 40(2), 383-394. https://doi.org/10.1007/s10514-015-9475-7
- Van, M., Franciosa, P. and Ceglarek, D. (2016), "Fault diagnosis and fault-tolerant control of uncertain robot manipulators using high-order sliding mode", Math. Probl. Eng.
- Wang, X., Li, X., Wang, J., Fang, X. and Zhu, X. (2016), "Data-driven model-free adaptive sliding mode control for the multi degree-of-freedom robotic exoskeleton", Inform. Sci., 327, 246-257. https://doi.org/10.1016/j.ins.2015.08.025
- Xia, X., Zhou, J., Xiao, J. and Xiao, H. (2016), "A novel identification method of Volterra series in rotorbearing system for fault diagnosis", Mech. Syst. Signal Pr., 66, 557-567.
- Zhang, K., Jiang, B., Cocquempot, V. and Zhang, H. (2013), "A framework of robust fault estimation observer design for continuous-time/discrete-time systems", Optim. Contr. Appl. Met., 34(4), 442-457. https://doi.org/10.1002/oca.2031
- Zhang, Q. and Besancon, G. (2008), "An adaptive observer for sensor fault estimation in a class of uniformly observable non-linear systems", J. Modell. Identific. Contr., 4(1), 37-43. https://doi.org/10.1504/IJMIC.2008.020998
- Zhang, K., Jiang, B. and Cocquempot, V. (2008), "Adaptive observer-based fast fault estimation", J. Contr. Autom. Syst., 6(3), 320-326.
- Zhang, J., Swain, A.K. and Nguang, S.K. (2013), "Robust sensor fault estimation scheme for satellite attitude control systems", J. Franklin Inst., 350(9), 2581-2604. https://doi.org/10.1016/j.jfranklin.2013.06.010