In this paper, the stability of a class of systems arising from neural control and fuzzy systems is studied. A new unifying stability criterion is presented using a very simple derivation. This result generalizes some previous results; some easily testable conditions are obtained.
TanakaK.An approach to stability criteria of neural-network control systems. IEEE Trans. Neural Networks, 1996, 7 (3), 629–642.
2.
TanakaK.SanoM.Fuzzy stability criteria of a class of nonlinear systems. Inf. Sci., 1993, 71, 3–26.
3.
TanakaK.SugenoM.Stability analysis and design of fuzzy control systems. Fuzzy Sets Systems, 1992, 45, 135–156.
4.
NguyenD.WidrowB.The track backer-upper: An example of self-learning in neural networks. In Proceedings of the International Joint Conference onNeural Networks, June 1989 Vol. 2, pp. 353–363.
5.
HornR. A.JohnsonC. R.Matrix Analysis, 1985 (Cambridge University Press, Cambridge).
6.
DesoerC. A.VidyasagarM.Feedback Systems: Input-Output Properties, 1975 (Academic Press, New York).
7.
BermanA.PlemmonsR. J.Nonnegative Matrices in the Mathematical Sciences, 1979 (Academic Press, New York).
