Journal article
Neural network architecture for control
IEEE Control Systems Magazine, v 8(2)
Apr 1988
Abstract
Two important computational features of neural networks are associative storage and retrieval of knowledge, and uniform rate of convergence of network dynamics independent of network dimension. It is indicated how these properties can be used for adaptive control through the use of neural network computation algorithms, and resulting computational advantages are outlined. The neuromorphic control approach is compared to model reference adaptive control on a specific example. It is shown that the utilization of neural networks for adaptive control offers definite speed advantages over traditional approaches for very-large-scale systems.< >
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58 citations in Scopus
Details
- Title
- Neural network architecture for control
- Creators
- A Guez - Drexel UniversityJ.L Eilbert - Drexel UniversityM Kam - Drexel University
- Publication Details
- IEEE Control Systems Magazine, v 8(2)
- Publisher
- IEEE
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Scopus ID
- 2-s2.0-0023999097
- Other Identifier
- 991019173521504721