Abstract
A new scheme to control processes, based on a layed neural network, was proposed. Adaptive and self-tuning features were achieved by modifying the weight for connections in the network through learning. As the learning sets of data, the relation gotten by experience and a global control policy were used simultaneously. The applicability of this scheme was confirmed by simulation of level control
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