卡尔曼滤波融合模糊PID算法优化反应釜温度控制

Temperature control analysis of reaction Kettle optimized by Kalman filter with fuzzy PID algorithm

为提高反应釜在生物发酵时对温度的抗干扰能力,以反应釜温度作为研究对象利用卡尔曼滤波融合模糊PID算法进行优化控制。根据能量守恒推导反应釜温度等效数学模型并进行线性化,利用模糊算法整定PID参数对线性化模型进行控制,经卡尔曼滤波预测矫正处理得到系统输出,在0.05和0.10噪声下分别对比PID与模糊PID法,分析该算法的控制精度以及抗干扰能力。结果表明,噪声大小在0.05和0.10时的温度响应偏差分别为0.701%和1.841%,明显优于其他两种算法。

This paper seeks to improve the anti-interference ability of the reactor kettle to the temperature during the biological fermentation, by taking the reactor temperature as the research object and using the Kalman filter fusion fuzzy PID(FL-KF-PID) algorithm to optimize the control. The study involves derivating and linearizing the equivalent mathematical model of the reactor temperature according to conservation of energy;adjusting PID parameter to the control of linearized model by fuzzy algorithm;obtaining the system output through Kalman filter prediction and correction;analyzing the control accuracy and anti-interference ability of the algorithm by comparing PID and fuzzy PID(FL-PID) algorithm under the noise condition of 0.05 and 0.10 respectively.The results show that the temperature response deviation are 0.701% and 1.841% at the noise level of 0.05 and 0.10, respectively, as which is significantly better than the other two algorithms. It is proved that FL-KF-PID algorithm has a better filtering effect on the noise at different noise levels, and improves the reactor temperature control accuracy and anti-interference ability. The results show that the temperature response deviation are 0.701% and 1.841% at the noise level of 0.05 and 0.10, respectively, as which is significantly better than the other two algorithms.