H.M. Khalid, and M. Akram, “Fault Modeling,
Detection and Classification using Fuzzy Logic,
Kalman Filter and Genetic Neuro-Fuzzy Systems,”
Asian Journal of Engineering, Sciences & Technology,
Vol. 1, No. 2, 45-57, 2011.
 K.O. Omali, M.N. Kabbaj, and M. Benbrahim.
“Fault Diagnosis for Manipulator Robot using
Observers-Based Approaches,” International Meeting
on Advanced Technologies in Energy and Electrical
Engineering, 1-9, 2018.
 A.T. Vemuri, M.M. Polycarpou, and S.A.
Diakourtis, “Neural Network Based Fault Detection in
Robotic Manipulators,” IEEE, Vol. 14, No. 2, 342-
 M. Abid, “Fault detection in nonlinear systems: An
observer based approach,” Ph.D. thesis, DuisburgEssen University, 2010.
 M.S. Khireddine, K. Chafaa, N. Slimane, and A.
Boutarfa, “Fault Diagnosis in robotic manipulators
using Artificial Neural Networks and Fuzzy logic,”
LRP & LEA Labs. Electronics Department, Batna
University Batna . IEEE, 2014.
 A.S. Rezazadeh, H.R. Koofigar, and S. Hosseinnia,
“Adaptive fault detection and isolation for a class of
robot manipulators with time-varying perturbation,”
Journal of Mechanical Science and Technology, 4901-
4911 Springer 2015.
 H-J. Ma, and G.-H. Yang, “Simultaneous fault
diagnosis for robot manipulators with actuator and
sensor faults,” Information Sciences 366, 12–30, 2016.
 C.T. Trung, H. M. Son, D. P. Nam, T. N. Long, D.
T. Toi, and P. A. Viet, “Fault Detection and Isolation
for Robot Manipulator Using Statistics,” International
Conference on System Science and Engineering
(ICSSE) IEEE, 340-343, 2017.
 M. Md Kamal and D. Yu, “Fault Detection and
Isolation using RBF Networks for Polymer Electrolyte
Membrane Fuel Cell,” World Academy of Science,
Engineering and Technology International Journal of
Electrical and Computer Engineering, Vol:7, No:4,pp.
 A.H. Issa, H.M. Hadi, “Intelligent Fault Detection
for Proton Exchange Membrane Fuel Cell PEMFC
Based on Artificial Neural Network ANN,” AlMansour University College / Proceeding of 15th
Scientific Conference pp. 207-218, 23-24, 2016.
 Daniel graupe, “Principles of Artificial Neural
Networks,” Second edition, World Scientific
Publishing Co. Pte. Ltd., Vol. 6, 2007.
 A.P. Engelbrecht, “Computational Intelligence,”
2nd Edition, John Wiley and Sons, Ltd., 2007.
 L.A. Bryan, and E.A. Bryan, “Programmable
Controllers: Theory and Implementation,” 2nd Edition,
Industrial Text Company, U.S.A, 1997.
 S. Dash, R. Rengaswamy, V.
Venkatasubramanian, “Fuzzy logic based trend
classification for fault diagnosis of chemical
processes,” Elsevier Science, Computers and Chemical
Engineering, Vol. 27, pp. 347-362, 2003.
 A. Telba, “Motor Speed Control Using FPGA,”
IEEE, Proceedings of the World
Congress on Engineering, London, UK, Vol. I. July 2
- 4, 2014.
 A. Konar, “Artificial Intelligence and Soft
Computing Behavioral and Cognitive Modeling of the
Human Brain,” CRC Press, 2000.
 K. Mehrotra, C.K. Mohan, and S. Ranka,
“Elements of Artificial Neural Networks,”
Massachusetts Institute of technology, 2000.
 A.H. Issa, and A.N. Abd, “Adaptive Inverse
Neural Network Based DC Motor Speed and Position
Control Using FPGA,” Diyala Journal of Engineering
Sciences, Vol. 11, No. 3, pp. 71-78, 2018.