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The diagonal recurrent neural networks (DRNN) is a powerful computational tools that have been used extensively in the areas of pattern recognition, systems modeling and identification. This paper proposes a self-tuning PID decoupling control based on DRNN neural networks for solving the time-varying coupling nonlinear control problems. The approach can on-line identify the controlled plant using...
Radial basis function (RBF) neural network (NN) is powerful computational tools, which have been used extensively in the areas of pattern recognition, systems modeling and identification due to the advantages of simple construction, adaptability and robustness. This paper presents a novel approach of single neuron PID model reference adaptive control (MRAC) control based on RBF neural network on-line...
Radial basis function (RBF) neural network (NN) is powerful computational tools that have been used extensively in the areas of pattern recognition, systems modeling and identification. This paper proposes an adaptive PID control method based on RBF neural network identification. This approach can on-line identify the controlled plant with the RBF neural network identifier and the weights of the adaptive...
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