J. M. Andjar and A. J. Barragn, A methodology to design stable nonlinear fuzzy control
systems, Fuzzy Sets and Systems, 154 (2005), 157-181.
 A. Aghili Ashtiani and M. B. Menhaj, Introducing a new pair of differentiable fuzzy norms
and its application to fuzzy relational function approximation, Proc. 10th Joint Conf. Information
Sciences, Salt Lake City, USA: World Scientific Publishing Co. ISBN: 978-981-270-
967-7, (2007), 1329-1336.
 A. Aghili Ashtiani and M. B. Menhaj, Numerical solution of fuzzy relational equations based
on smooth fuzzy norms, Soft Computing, 14(6) (2010), 545-557.
 X. Ban, X. Z. Gao, X. Huang and A. V. Vasilakos, Stability analysis of the simplest Takagi–
Sugeno fuzzy control system using circle criterion, Information Sciences, 177(20) (2007),
 J. Chen and L. Chen, Study on stability of fuzzy closed-loop control systems, Fuzzy Sets and
Systems, 57(2) (1993), 159-168.
 T. Furuhashi, H. Kakami, J. Peters and W. Pedrycz, A stability analysis of fuzzy control
system using a generalized fuzzy petri net model, IEEE World Congress on Computational
Intelligence, (1998), 95-100.
 T. Hasegawa and T. Furuhashi, Stability analysis of fuzzy control systems simplified as a
discrete system, Int. J. Control and Cybernetics, 27(4) (1998), 565-577.
 K. Hirota, H. Nobuhara, K. Kawamoto and S. I. Yoshida On a lossy image compression/
reconstruction method based on fuzzy relational equation, Iranian Journal of Fuzzy Systems,
1(2) (2004), 33-42.
 J. B. Kiszka, M. M. Gupta and P. N. Nikiforuk, Energetic stability of fuzzy dynamic systems,
IEEE Transactions on Systems, Man and Cybernetics, 15 (1985), 783-792.
 A. Kandel, Y. Luo and Y. Q. Zhang, Stability analysis of fuzzy control systems, Fuzzy Sets
and Systems, 105 (1999), 33-48.
 C. Kolodziej and R. Priemer, Stability analysis of fuzzy systems, Journal of the Franklin
Institute, 336 (1999), 851-873.
 T. Leephakpreeda and C. Batur, Stability analysis of a fuzzy control system, Thammasat Int.
J. Science and Technology, 2(l) (1997), 1-5.
 W. Pedrycz, An identification algorithm in fuzzy relational systems, Fuzzy Sets and Systems,
13 (1984), 153-167.
 J. N. Ridley, I. S. Shaw and J. J. Kruger, Probabilistic fuzzy model for dynamic systems,
Electronics Letters, 24 (1988), 890-892.
 A. A. Suratgar and S. K. Y. Nikravesh, A new method for linguistic modeling with stability
analysis and applications, Intelligent automation and soft computing, 15(3) (2009), 329-342.
 A. A. Suratgar and S. K. Y. Nikravesh, Potential energy based stability analysis of fuzzy
linguistic systems, Iranian Journal of Fuzzy Systems, 2(1) (2005), 67-74.
 A. A. Suratgar and S. K. Y. Nikravesh, Necessary and sufficient conditions for asymptotic
stability of a class of applied nonlinear dynamical systems, Proc. 10th IEEE Int. Conf. Electronics,
Circuits and Systems, 3 (ICECS 2003), 1062-1065.
 A. A. Suratgar and S. K. Y. Nikravesh, A new sufficient condition for stability of fuzzy
systems, Proc. of Iranian Conf. Electrical Engineering, (2002), 441-445.
 E. Sanchez, Resolution of composite fuzzy relation equations, Information and Control, 30(1)
 T. ˇ Sijak, S. Teˇsnjak and O. Kuljaca, Stability analysis of fuzzy control system using describing
function method, Proc. 9th Mediterranean Conf. Control and Automation, 2001.