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Parameters optimization of PID controller based on Kalman filter and ant colony algorithm

机译:基于卡尔曼滤波和蚁群算法的PID控制器参数优化

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摘要

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.
机译:为了在PID控制器中优化参数并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了改进,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。该方法通过蚁群算法优化了PID参数,并通过卡尔曼滤波器抑制了过程噪声和测量噪声。仿真结果表明,改进的滤波方法具有较高的效率,实现了全局PID参数的优化,减少了系统过程噪声和测量噪声引起的误差,大大提高了控制效果。

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