基于改进粒子群算法的泄漏容腔高精度压力控制OA

To solve the problems of low efficiency and poor adaptability to complex operating conditions in traditional tuning of pressure controller parameters due to the relying heavily on manual trial-and-error based on empirical experience,the scheme for optimizing controller parameters based on the improved particle swarm optimization(PSO)algorithm was proposed.By the proposed algorithm,the global search capability and optimization performance were improved by removing the velocity term in the traditional position update formulation and incorporating chaotic mapping and somersault foraging strategies.The simulation comparison results on 10 benchmark functions show that the improved algorithm is more advantageous in terms of overall performance.The pressure control results for 30 L chamber show that compared to the trial-and-error method,the optimization method achieves 56.8％reduction in the steady-state error of system under the leakage condition.When the optimized parameters are further applied to the step pressure control under closed condition and constant leakage condition,the system steady-state errors are less than 40 Pa and 90 Pa,respectively,which illuminates that the optimization scheme has good adaptability under different conditions.