Fault-Tolerant Damage Control of Nonlinear Structures Using Artificial Intelligence

Document Type : Research Papers


1 Department of Civil Engineering, University of Gonabad, Gonabad, Iran

2 Associate Professor, Department of Civil Engineering, Faculty of Engineering, Ferdowsi University Of Mashhad (FUM)

3 Professor, Department of Civil Engineering, Ferdowsi University of Mashhad, Iran


In this paper, the artificial intelligence is employed to design a Fault-Tolerant Controller (FTC) for structural vibrations. The FTC is designed to reduce the probability of damage considering sensor fault. For this purpose, Neural Networks (NNs) are used as fault detection and accommodation and fuzzy logic is used as a controller. This control strategy requires two groups of neural networks. The first group of neural networks finds the faulty sensor by estimating the structural responses and comparing them with the responses obtained from the sensors. The second group has the task of estimating the response of the faulty sensor using data obtained from healthy sensors. To evaluate this method, the time history analysis of a 3-story benchmark building equipped with accelerometers and active actuators has been used. This evaluation is based on determining the probability of structural damage and the generation of fragility curves under forty ground motions. To develop fragility curves, the criteria specified in the FIMA 356 (IO, LS and CP) for the moment frame based on the inter-story drift are used. This study show that in the absence of the neural networks, sensor fault reduces the performance of the fuzzy controller and it is even possible to increase the structural responses compared to the structure without the controller. In addition, results demonstrate that the proposed control strategy can rectify the deterioration of sensor faults and decrease the probability of failure.


Abdollahzadeh, G.R., Asghari, A.A. and Sazjini, M. (2015). "Seismic fragility assessment of special truss moment frames (STMF) using the capacity spectrum method", Civil Engineering Infrastructures Journal, 48(1), 1-8.
Baghban, A., Karamodin, A. and Haji-Kazemi, H. (2015). "Nonlinear control of structure using neuro-predictive algorithm", Smart Structures and Systems,16(6), 1133-1145.
Bazzurro, P. and Cornell, C.A. (1994). "Seismic hazard analysis of nonlinear structures, I: Methodology", Journal of Structural Engineering, 120(11), 3320-3344.
Choi, Y.-C., Son, J.-H. and Ahn, H.-S. (2015). "Fault detection and isolation for a small CMG-based satellite: A fuzzy Q-learning approach", Aerospace Science and Technology, 47, 340-355.
Erberik, M.A. and Elnashai, A.S. (2004). "Fragility analysis of flat-slab structures", Engineering Structures, 26(7), 937-948.
FEMA-356. (2000). Prestandard and commentary for the seismic rehabilation of buildings, USA, Federal Emergency Management Agency.
Fonod, R., Henry, D., Charbonnel, C., Bornschlegl, E., Losa, D. and Bennani, S. (2015). "Robust FDI for fault-tolerant thrust allocation with application to spacecraft rendezvous", Control Engineering Practice, 42, 12-27.
Ghaffarzadeh, H. (2013). "Semi-active structural fuzzy control with MR dampers subjected to near-fault ground motions having forward directivity and fling step", Smart Structures and Systems, 12(6), 595-617.
Karamodin, A., Irani, F. and  Baghban, A. (2012). "Effectiveness of a fuzzy controller on the damage index of nonlinear benchmark buildings", Scientia Iranica, 19(1), 1-10.
Kazantzi, A.K., Righiniotis, T.D. and Chryssanthopoulos, M.K. (2008). "Fragility and hazard analysis of a welded steel moment resisting frame", Journal of Earthquake Engineering, 12(4), 596-615.
Kwon, O.-S. and Elnashai, A. (2006). "The effect of material and ground motion uncertainty on the seismic vulnerability curves of RC structure", Engineering Structures, 28(2), 289-303.
Lan, J. and Patton, R.J. (2016). "A new strategy for integration of fault estimation within fault-tolerant control", Automatica, 69, 48-59.
Lebreton, C., Damour, C., Benne, M., Grondin-Perez, B. and Chabriat, J.-P. (2016). "Passive fault tolerant control of PEMFC air feeding system", International Journal of Hydrogen Energy, 41(34), 15615-15621.
Mohammadizadeh, M.R., Vahidi, K. and Ronagh, H.R. (2018). "Seismic reliability analysis of offshore fixed platforms using incremental dynamic analysis", Civil Engineering Infrastructures Journal, 51(2), 229-251.
Ohtori, Y., Christenson, R.E., Spencer, B.F. and Dyke, S.J. (2004). "Benchmark control problems for seismically excited nonlinear buildings", Journal of Engineering Mechanics, 130(4), 366-387.
Padgett, J.E. and DesRoches, R. (2008). "Methodology for the development of analytical fragility curves for retrofitted bridges", Earthquake Engineering and Structural Dynamics, 37(8), 1157-1174.
Raji, R., Hadidi, A., Ghaffarzadeh, H. and Safari A. (2018). "Robust decentralized control of structures using thr LMI ∞ controller with uncertainties", Smart Structures and Systems, 22(5), 547-560.
Schuh, M., Zgorzelski, M. and Lunze, J. (2015). "Experimental evaluation of an active fault–tolerant control method", Control Engineering Practice, 43, 1-11.
Schulte, H. and Gauterin, E. (2015). "Input-to-state stability condition for passive fault-tolerant control of wave and wind energy converters", IFAC-Papers On Line, 48(21), 257-262.
Shen, Q., Jiang, B., Shi, P. and Lim, C.C. (2014). "Novel neural networks-based fault tolerant control scheme with fault alarm", IEEE Transactions on Cybernetics, 44(11), 2190-2201.
Somerville, P., Nf, S., Punyamurthula, S. and Ji, S. (1997). Development of ground motion time histories for phase 2 of the FEMA/SAC steel project, SAC Joint Venture, a partnership of: Structural Engineers Association of California, Applied Technology Council, California Universities for Research in Earthquake Engineering,  Report No. SAC/BD-97/04.