自抗扰控制器在强干扰系统和大时滞条件下的控制效果不好，主要影响因素是静态参数机制，为此设计了一种基于差分进化算法和粒子群算法联合优化的自抗扰控制器。使用粒子群算法对自抗扰控制器中抗扩张状态观测器的动量估计系数进行在线优化，使用误差阈值触发启动的伺服机制提高动态优化的计算速度，并使用差分进化算法的变异、交叉和选择算子提高粒子群算法的多样性，防止陷入局部最优值以提高算法的收敛精度。在热工时滞系统中的实验结果表明，改进后的算法在强干扰系统和大时滞条件下的控制效果得到提高，抗干扰性能和鲁棒性得到提高。%Since the active disturbance rejection controller in strong interference system and under large?delay condition has bad control effect due to the influence of the static parameter mechanism,an active disturbance rejection controller based on the joint optimization of the particle swarm optimization algorithm and difference evolution algorithm was designed. The particle swarm optimization algorithm is used to optimize the momentum estimation coefficient of the anti?expansion state observer in the controller online. The servo mechanism started by the error threshold trigger is adopted to improve the computation speed of the dynamic optimization. The mutation,crossover and selection operators of the difference evolution algorithm are employed to im?prove the diversity of the particle swarm optimization algorithm and prevent it from falling into the local optimum,so as to im?prove the convergence precision of the algorithm. The experimental results of the thermal time delay system show that the control effect of the improved controller in strong interference system and under large?delay condition is improved,and the anti?jamming performance and robustness are enhanced.
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