Journal
ASIAN JOURNAL OF CONTROL
Volume 12, Issue 1, Pages 96-102Publisher
CHINESE AUTOMATIC CONTROL SOC
DOI: 10.1002/asjc.160
Keywords
Neural network; decentralized control; global stability; backstepping
Categories
Funding
- National Natural Science Foundation of China [60804021]
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A globally stable decentralized adaptive backstepping neural network tracking control scheme is designed for a class of large-scale systems with mismatched interconnections. Under the assumption that the subsystems share the reference signals from the other subsystems, neural networks are used to approximate the unknown interconnections dependent on all reference signals such that the NN approximation domain can be determined a priori based on the bounds of reference signals. The proposed control approach can guarantee that all closed-loop signals are globally uniformly ultimately bounded and that the tracking errors converge to a small residual set around the origin.
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