To address the complexity and excessive reliance on expert experience in tuning fuzzy Proportional-Integral-Derivative (PID) controller parameters, this study proposes a variable-rate spraying control system that integrates an improved Beetle Antennae Search (IBAS) algorithm with fuzzy PID control. To evaluate the feasibility of the system, a mathematical transfer function of the variable-rate spraying system was constructed, and a flow control simulation platform was established for simulation analysis. To overcome the limitations of conventional BAS, which is prone to premature convergence and limited search precision, the IBAS algorithm was developed. The improvements include a hybrid disturbance strategy to enhance individual search capability and a simulated annealing mechanism to prevent the algorithm from being trapped in local optima. Using the IBAS algorithm, the proportional and quantization factors of the fuzzy PID controller were optimized offline to obtain the optimal parameters. The IBAS-fuzzy PID controller was then compared in simulation with conventional PID, fuzzy PID, and BAS-optimized fuzzy PID controllers. The simulation results demonstrated that the IBAS-fuzzy PID algorithm achieved higher flow control accuracy than existing methods. To further validate the effectiveness of the improved algorithm under practical conditions, field experiments were conducted. The results indicated that the IBAS-optimized fuzzy PID controller outperformed the three other control methods in terms of flow control accuracy. Overall, both simulation and field results confirm that the proposed IBAS algorithm for fuzzy PID parameter optimization significantly enhances response speed, control precision, and overshoot reduction, providing a novel approach and potential application for variable-rate spraying technology.