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传统的Ziegler-Nichols(Z-N)PID参数整定法往往不能达到最佳的控制性能.提出一种免疫果蝇优化算法(Immune Fruit Fly Optimization Algorithm,IFOA),采用综合性能指标时间与偏差绝对值乘积积分(ITAE)作为适应度函数,应用于PID控制参数优化.在果蝇嗅觉搜索模式中选取最佳果蝇个体作为免疫疫苗;果蝇算法视觉搜索模式中加入人工免疫算法的免疫选择和疫苗接种等免疫操作环节,有助于避免果蝇优化算法陷入局部最优解,并克服了人工免疫算法计算繁琐效率低下的缺点;采用4种基准函数对所提出算法的性能进行了测试,并应用于PID控制器的参数整定.仿真结果表明,所提算法具有良好稳定性,收敛精度高,应用于PID控制参数优化可行且有效.“,”The traditional Z-N (Ziegler-Nichols) method usually fails to achieve the best control performance for tuning PID parameters. Therefore, an immune fruit fly optimization algorithm (IFOA) with the error performance criterion of ITAE as the fitness function for PID parameter optimization is proposed. Firstly, select the best individuals as immune vaccines in the fly olfactory search mode. Then, introduce the immune vaccination and the immune selection mechanism in the visual search mode to avoid the fruit fly optimization algorithm falling into premature and overcome the shortcomings of cumbersome and inefficient calculations of the artificial immune algorithm. Finally, the performance of the hybrid algorithm is tested with 4 benchmarks, and applied in PID parameter tuning. Simulation results show that the IFOA owns good stability and higher precision, and is feasible and effective in PID control parameter optimization.