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Piecewise linear controller improving its own reliability
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DOI：10.1016/0959-1524(95)00049-6.png)
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摘要
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Although the capability of neural networks in nonlinear dynamics modelling is well-established, the reliability of the output heavily depends on the training data. The reliability is a serious problem in applying it to real problems. in this paper, we propose a radial basis functions network (RBFN) which evaluates its own reliability and improves itself recursively. This network approximates the input-output relationships with a piecewise linear regression. An adaptive internal model control algorithm in which the reliability of the model is used to tune the controller performance, is also proposed.
Keyword:
neural network
piecewise linear regression
nonlinear control
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论文数:
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被引数:
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