Abstract
In this paper, the authors describe a novel fuzzy adaptation method to construct or change the rules in the fuzzy controller rule base table. The objective of the fuzzy logic adaptation mechanism (FLAM) is to change the rules definition in the FLC rule base table, according to the comparison between a reference model output signal and the system output. So, the learning algorithm defines the output linguistic values for each rule, based on a desired trajectory. They show the efficiency of this method in a TMS320C30 DSP-based speed fuzzy control of a permanent magnet synchronous motor (PMSM). The fuzzy logic adaptive strategy can be readily implemented. It has very fast learning features and very good tracking characteristics even under severe variations of the system parameters. At each sample instant, the FLAM will affect only the active rules.
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