Neural network control design for a rigid-link electrically driven robot

2003 ◽  
Vol 217 (2) ◽  
pp. 99-107 ◽  
Author(s):  
S N Huang ◽  
K K Tan ◽  
T H Lee
Keyword(s):  
Neural Network ◽  
Control Design ◽  
Network Control ◽  
Second Step ◽  
Neural Network Control ◽  
Linear Dynamics ◽  
Rigid Link ◽  
Non Linear ◽  
Robot Systems ◽  
The Stability

In this paper, a back-stepping scheme for rigid-link electrically driven (RLED) robot systems is proposed. A two-step controller is presented: the first step is a virtual controller, while the second step is an actual one. A neural network is used to approximate the unknown non-linear dynamics in the system. The stability can be guaranteed by using a rigid proof. A simulation is used to illustrate the effectiveness of the proposed algorithm.

Neural network control of a non-linear heater battery

1994 ◽  
Vol 15 (3) ◽  
pp. 119-129 ◽  
Author(s):  
S.J. Hepworth ◽  
A.L. Dexter ◽  
S T P Willis
Keyword(s):  
Neural Network ◽  
Network Control ◽  
Neural Network Control ◽  
Non Linear

New stability criteria for a class of systems arising in neural network control and fuzzy systems

2000 ◽  
Vol 214 (1) ◽  
pp. 1-8
Author(s):  
Y Fang ◽  
T G Kincaid ◽  
S Li
Keyword(s):  
Neural Network ◽  
Stability Criterion ◽  
Fuzzy Systems ◽  
Neural Control ◽  
Network Control ◽  
Neural Network Control ◽  
Stability Criteria ◽  
Simple Derivation ◽  
The Stability

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.

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