改进卡尔曼滤波的PID控制

传统的基于卡尔曼滤波算法的PID控制，在滤除控制过程中和测量过程中的噪声干扰方面效果很好。但系统的收敛速度、超调等方面还存在问题，这主要是PID参数没有达到最优。针对卡尔曼PID的参数优化问题，结合遗传算法优化PID参数，引入增量的分段控制改进控制信号u]的组成结构。经过Matlab仿真验证，方法数据量少、参数优化快、系统收敛快、超调小，方法可行。

Improved Kalman filtering in PID control

The traditional PID control based on the Kalman filtering algorithm, is very good in the filtration of the controlled noise and the measuring noise. But there are some problems in the systematic convergence rate, overshoot, et al. It is because the PID parameter has not achieved optimally. In order to solve this problem, this paper combines genetic algorithm, and introduces the increment subsec- tion control to improve the structure of control signal. After Matlab simulation, the proposed method has few data, faster parameter opti- mization, faster system convergence and smaller overshoot. The method is simple and available.