Title :
A note on stability and stabilizability of fuzzy-neural-linear control systems
Author_Institution :
Dept. of Mech. Syst. Eng., Kanazawa Univ., Japan
Abstract :
This paper discusses ther stability analysis of fuzzy-neural-linear (FNL) control systems by the Lyapunov approach. The relationship between the dynamics of neural network (NN) systems, that of fuzzy systems and that of linear systems is considered. Furthermore, it is shown that stability conditions for fuzzy systems can also be applied to NN systems and linear systems. Finally, the stability of FNL control systems is analyzed by using the stability conditions
Keywords :
Lyapunov methods; fuzzy control; fuzzy neural nets; neural nets; stability; Lyapunov approach; fuzzy-neural-linear control systems; neural network; stability; stability analysis; stabilizability; Control system analysis; Control systems; Fuzzy control; Fuzzy systems; Linear systems; Mechanical systems; Neural networks; Nonlinear systems; Stability analysis; Systems engineering and theory;
Conference_Titel :
Fuzzy Information Processing Society Biannual Conference, 1994. Industrial Fuzzy Control and Intelligent Systems Conference, and the NASA Joint Technology Workshop on Neural Networks and Fuzzy Logic,
Conference_Location :
San Antonio, TX
Print_ISBN :
0-7803-2125-1
DOI :
10.1109/IJCF.1994.375141
