Multi-objective Genetic Algorithm Optimization of Forward Speed of Fuzzy Control System for Combine Harvester
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    Abstract:

    The operating performance of combine harvester is not usually satisfactory because of the subjectivity of parameters design to the fuzzy control system of forward speed. Taking a combine harvester as research objective, the paper constructs the simulation model of multi-parameters fuzzy control system and establishes the optimized objective functions for control performance and harvesting performance to evaluate operating performance of combine harvester. A multi-objective genetic algorithm was used to optimize membership functions and parameters’ factors of conveyer trough, cutting table auger and tangential threshing rotor influenced on forward speed in the fuzzy control system. By comparing to the model simulation and analyzing the two groups of experimental data before and after optimization, the results proved that after the control system optimized, the control performance still presented good under the conditions of external interference, and the average unit loss indexes reduced from 1.45% and 1.26% to 1.12% and 1.14%, respectively. The feeding quantity did not change much, and the whole operating performance was improved.

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History
  • Received:August 27,2014
  • Revised:
  • Adopted:
  • Online: May 10,2015
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