Simulation Research on Adaptive Control System of Combine Harvester Feeding Rate Based on Fuzzy PID

Abstract

During field operations, combine harvesters frequently encounter significant fluctuations in feeding rates attributable to the stochastic nature of crop density and uneven growth patterns. These irregularities often precipitate critical mechanical failures, such as threshing drum blockages and engine stalling. To mitigate these operational risks, this study proposes a robust adaptive control strategy for feeding rate regulation rooted in fuzzy logic. Initially, a mathematical model of the system dynamics is constructed by analyzing the nonlinear coupling between the harvester’s forward speed and the feeding rate, incorporating characteristics of significant inertia and pure time delay. Addressing the inherent limitations of conventional PID algorithms—specifically their inadequate parameter adaptability and weak disturbance rejection under complex, time-varying conditions—a fuzzy adaptive PID controller is designed. This controller utilizes the feeding rate error () and its rate of change  as inputs to facilitate online, real-time tuning of the proportional, integral , and derivative parameters via a fuzzy inference mechanism. Simulation experiments conducted on the MATLAB/Simulink platform demonstrate that, compared to traditional PID control, the proposed system reduces overshoot by approximately 14.2% (from 18.3% to 4.1%) when subjected to step changes in crop density. Furthermore, the settling time is significantly truncated, and steady-state error is effectively eliminated. These results corroborate that the proposed control strategy exhibits superior robustness and dynamic tracking capabilities, thereby satisfying the rigorous requirements for automated operation in modern precision agriculture.