卡尔曼滤波在电动滑台位置实时补偿中的应用

Application of Kalman Filter in Real-time Compensation of Electric Sliding Table Position

由于控制系统的轨迹跟踪误差以及测量装置存在的高斯噪声,使得电动滑台位置控制误差累积。针对这一问题,设计了基于卡尔曼滤波的位置实时补偿控制系统。通过改进梯形速度算法设计电动滑台的运动控制律,从而得到滑台的期望轨迹序列。结合测量装置测得的编码器值以及系统状态方程的预测值,采用卡尔曼滤波算法得到当前时刻滑台位置的最优估计值。并以此为基准得到到达下一时刻期望位置所需的位移增量,从而实现对当前时刻位置误差的补偿。实验结果表明,该系统可以抑制噪声,得到稳定可靠的系统状态值,同时提高了控制系统的轨迹跟踪精度。

The trajectory tracking error of the control system and the Gaussian noise present in the measuring device cause the electric sliding table position control error to accumulate.Aiming at this problem,a position real-time compensation control system based on Kalman filtering was designed.The motion control law of the electric sliding table was designed by improving the trapezoidal speed algorithm to obtain the desired trajectory sequence of the sliding table.Combined with the measured encoder value and the predicted value of the system state equation,the optimal estimation of the slide position at the current moment was obtained by using the Kalman filter algorithm.Based on this,the displacement increment required to reach the desired position at the next moment was obtained,thereby realizing the compensation of the current position error.The experimental results show that the system can suppress noise,obtain stable and reliable system state value,and improve the tracking accuracy of the control system.