To address the issues of large overshoot, slow response, poor stability, and suboptimal control performance of traditional PID algorithms caused by the nonlinear relationship between the rotational speed and output flow rate of micro screw pump motors, this study proposes a PID parameter optimization method based on an improved spider wasp optimizer algorithm. First, this method incorporates the Tent chaotic mapping into the Spider Wasp Optimizer algorithm (SWO) to enhance initial population diversity, integrates differential evolution strategies to accelerate convergence, and employs Levy flight to boost local search capabilities, thereby balancing global exploration with local exploitation. Subsequently, comparative validation using 12 benchmark functions demonstrates that the improved algorithm (ISWO) outperforms SWO, PSO, SA, GOOSE, and CPO across metrics including mean, standard deviation, and Wilcoxon rank-sum test. Finally, integrating ISWO with PID control yields ISWO-PID, applied to a screw pump model. Simulation results demonstrate superior optimization efficiency and control performance: runtime was reduced by over 60% compared to benchmark algorithms, with enhanced system robustness and adaptability.