GENERALIZED ALGORITHM OF COMBINE PROCESS ADJUSTMENT BASED ON FUZZY KNOWLEDGE MODELS
Abstract
The problem of creating the mechanism of an expert system fuzzy inference meant for decision-making on the combine process adjustment is considered. The fuzzy inference algorithm is based on the domain models of ‘prior configuration’ and ‘process adjustment’. Fuzzification, composition, and defuzzification are general stages of the problem solution. The problem-solving mechanism is based on the deductive scheme (for the prior configuration problem), and on the inductive one (for the process adjustment problem). The specific feature of the proposed problem-solving algorithm is the hypothesis testing of emerging combining process non-conformances under the machine parameter variations. In this case, the validity of the exception condition generation when an additional breakdown in the technological process occurs is checked. The developed fuzzy inference algorithm and the domain model based on the fuzzy expert knowledge permit to approach considerably the solution to the decision-making automation problem under the combine process adjustment in the field environment.
About the Authors
Valery Petrovich Dimitrov
Don State Technical University.
Russian Federation
Russian Federation
Lyudmila Victorovna Borisova
Don State Technical University.
Russian Federation
Russian Federation
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Review
For citations:
Dimitrov V.P., Borisova L.V. GENERALIZED ALGORITHM OF COMBINE PROCESS ADJUSTMENT BASED ON FUZZY KNOWLEDGE MODELS. Vestnik of Don State Technical University. 2013;13(7-8):65-74. (In Russ.) https://doi.org/10.12737/2022
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