Intelligent Controlling Model for Cleaning of Rice–Wheat Combine Harvester Based on Multi-Objective Optimization Particle Swarm Method

Abstract

Intelligent control has become an important research direction of a combine harvester. However, the impact of cleaning control parameters in rice–wheat combine harvesters on cleaning loss rate and impurity rate often tends to be contradictory. In this paper, an intelligent controlling model based on multi-objective optimization particle swarm (MOPSO) was constructed to solve this problem. The control model can real-time monitor the cleaning performance such as the cleaning loss rate and impurity rate and regulate the cleaning operation conditions such as the angle of the air distributor plate, the opening of the upper sieve and the fan speed. The field operation experiment of 10[Formula: see text]kg feeding rice–wheat combine harvester proves that the control model based on MOPSO is more effective than the model based on fuzzy control.