Abstract
A frequently used learning algorithm for self-organising fuzzy logic control has been analysed and found to be inadequate for some applications. The key problem is how to gain the credit value for control rule modification. A new type of learning algorithm is proposed. Some supervision rules are given to secure rule modifications. A new approach is derived to calculate the credit value for the rule generation and modification. Simulation studies for controlling different process models and different model parameters are demonstrated.
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