DocumentCode :
2206746
Title :
Neural-network-inverse-model control strategy-discrete-time analysis for relative order one system
Author :
Hussain, Mohamed Azlan
Author_Institution :
Dept. of Chem. Eng., Malaya Univ., Kuala Lumpur, Malaysia
Volume :
3
fYear :
1998
fDate :
21-26 Jun 1998
Firstpage :
1410
Abstract :
We initially discuss the relationship between the neural-network-inverse-based control approaches and the globally linearised control approach, the closed loop formulation of which is utilised in the formulation of the neural-network-based closed-loop state space representation for a relative order one system. Next the stability analysis of the closed loop system for this system, using Lyapunov´s technique, is discussed and some simulation studies presented
Keywords :
Lyapunov methods; closed loop systems; control system analysis; discrete time systems; neurocontrollers; stability; state-space methods; Lyapunov´s technique; discrete-time analysis; globally linearised control; neural-network-based closed-loop state space representation; neural-network-inverse-model control strategy; relative order one system; stability analysis; Chemical analysis; Control system synthesis; Electronic mail; Inverse problems; Network synthesis; Neural networks; Neurofeedback; Nonlinear control systems; Stability analysis; State-space methods;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference, 1998. Proceedings of the 1998
Conference_Location :
Philadelphia, PA
ISSN :
0743-1619
Print_ISBN :
0-7803-4530-4
Type :
conf
DOI :
10.1109/ACC.1998.707056
Filename :
707056
Link To Document :
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