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The PID control of RBF-NN is taken for the nonlinear system. Due to the low quality of clustering in the clustering algorithm of the traditional RBF-NN, the rate of convergence is directly influenced by the initial value. In this paper, the quality of the clustering has been raised and the initial value has been optimized through the improvements of the clustering algorithm by taking the K-means-algorithm...
This paper presents a neural network proportion integral differential (PID) controller for automatic gauge control (AGC) System of rolling mill, it is an high non-linear and time-varying system. The traditional PID controller has the invariable parameters. However in the actual factory, the environment of the controlled object is often changed. If the three parameters of PID controller can't adjusted...
Power system installed with SSSC is a large-scale nonlinear, indeterminist, multivariable system, and the traditional PI controller has a limited application in some cases because of its non-adaptive parameters. This paper presents the design of a neuron-controller for a SSSC that augments the conventional PI controller. The neuron controller uses adaptive critic design (ACD) with emphasis on dual...
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