基于卡尔曼滤波和蚁群算法的PID控制器参数优化

Li Shelei, Liu Haitao
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引用次数: 0

摘要

为了优化PID控制器的参数,抑制过程噪声和测量噪声,引入蚁群算法对卡尔曼滤波方法进行改进,提出了基于卡尔曼滤波和蚁群算法的PID控制器参数优化方法。该方法采用蚁群算法优化PID参数,通过卡尔曼滤波抑制过程噪声和测量噪声。仿真结果表明,改进后的滤波方法效率高,实现了PID参数的全局优化,降低了系统过程噪声和测量噪声引起的误差,控制效果大大改善和增强。
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Parameters optimization of PID controller based on Kalman filter and ant colony algorithm
For optimizing parameters and restraining process noise and measurement noise in PID controller, ant colony algorithm was introduced to improve Kalman filtering method, and the PID controller parameters optimization method based on Kalman filter and ant colony algorithm was put forward. This method optimized PID parameters by ant colony algorithm, and restrained process noise and measurement noise by Kalman filter. The simulation result showed that, the improved filtering method had high efficiency, a global PID parameters optimization was achieved, the error caused by system process noise and measurement noise was reduced, the control effect was greatly improved and enhanced.
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