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SOCO
2002
Springer

A dynamically-constructed fuzzy neural controller for direct model reference adaptive control of multi-input-multi-output nonlin

9 years 2 months ago
A dynamically-constructed fuzzy neural controller for direct model reference adaptive control of multi-input-multi-output nonlin
Conventional industrial control systems are in majority based on the single-input-single-output design principle with linearized models of the processes. However, most industrial processes are nonlinear and multivariable with strong mutual interactions between process variables that often results in large robustness margins, and in some cases, extremely poor performance of the controller. To improve control accuracy and robustness to disturbances and noise, new design strategies are necessary to overcome problems caused by nonlinearity and mutual interactions. We propose to use a dynamicallyconstructed, feedback fuzzy neural controller (DCF-FNC) from the input
Yakov Frayman, Lipo Wang
Added 23 Dec 2010
Updated 23 Dec 2010
Type Journal
Year 2002
Where SOCO
Authors Yakov Frayman, Lipo Wang
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