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This paper discussed and researched the structure and algorithm of fuzzy neural network controller based on the character of fuzzy logic and neural network theory. For the nonlinear system characteristics of uncertainty, high order and hysteresis, this paper used the fuzzy neural network technology to control nonlinear system and improved the control quality obviously. Take the single inverted pendulum...
A new kind of intelligent control is discussed, namely, human simulated intelligent control (HSIC), which hierarchically include three levels: centrum chief level (CC), organizing and coordinating level (OC), and unit control level (UC). Then the control problem of arbitrary switch control of circular-rail double pendulum (CRDP) is studied. Finally, the control system for this control problem is designed...
In the conventional variable universe fuzzy control system, it was hard to select the function models of the contraction-expansion factors and parameters of the models. A new variable universe fuzzy control algorithm, to achieve the contraction-expansion of universes by fuzzy neural network in place of the function models, was proposed in this paper. The algorithm, with the semantic characteristics...
The neural extended Kalman filter (NEKF) is an adaptive state estimation technique. The neural network training occurs while the system is in operation then the NEKF is able to learn on-line. The NEKF identifies mismodeled dynamics of the system to improve state estimation by learning the differences between the previous model and the measurements that it observes. The prediction from the NEKF can...
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