基于粒子群优化算法的改进降全阶切换自抗扰控制OA

[Objective]This study addresses the challenges of slow dynamic response,insufficient tracking accuracy,and complex parameter tuning in permanent magnet synchronous linear motor under multi-source disturbances.Reduced-full-order switched active disturbance rejection control based on particle swarm optimization(PSO-RSADRC)algorithm is proposed to enhance control precision.[Methods]First,an intelligent switching active disturbance rejection control(SADRC)architecture was constructed,optimizing disturbance rejection performance through linear/nonlinear dynamic switching.Then,reduced-full-order SADRC(RSADRC)to simplify the observer structure and reduce parameter coupling was proposed.Finally,to address the multi-parameter coupling issue in the nonlinear error feedback module,a PSO-RSADRC approach was developed,and simulation and experimental validation were conducted based on a fourth-order S-curve motion planning model.[Results]Simulation results demonstrated that PSO-RSADRC achieved an integral time-weighted absolute error of 0.95 and maximum dynamic error of 19 μm under 1 A step disturbance,improving precision by 98%compared to conventional linear ADRC.During platform validation,the settling time was reduced to 57 ms with a 32%enhancement in response speed.[Conclusion]The proposed PSO-RSADRC strategy effectively resolves precision motion control challenges under multi-source disturbances,demonstrating significantly superior parameter tuning efficiency and disturbance rejection robustness compared to conventional methods.This solution provides a reliable technical approach for high-precision industrial applications such as microelectronics packaging.