基于卡尔曼滤波的倒立摆控制系统噪声抑制

在二级倒立摆稳摆控制中,摆杆的角度信号受到测量噪音污染,通过差分获取角速度时,该噪音被放大,导致稳摆控制器的输出产生较大的随机波动,同时电机作为执行器,也混入了较大的过程噪音.这两种噪音使系统出现较强抖动,既不利于摆杆稳定,也缩短了电机寿命.对此,将稳态卡尔曼滤波器与渐消记忆法结合起来,找到了确定稳态卡尔曼滤波器增益矩阵的有效方法,既克服了模型误差,又满足实时性要求,减小了电机抖动,取得了较好的效果.

Noise suppression of inverted pendulum system based on Kalman filter

In the stabilization of inverted pendulum, the angle is polluted by the measurement noise. When making use of
the angle signal to calculate the angular velocity through difference, the noise is amplified, which makes the controller output
oscillate randomly. Besides, the motor, as the actuator, is polluted by the plant noise, leads to the strong system oscillation,
which not only is harmful for pendulum stabilization, but also reduces the motor’s service life. Combining the steady-state
Kalman filter with the disappearing memory method, the effective way to determine the Kalman filter gain matrix is found
out, which overcomes the model error, satisfies the real time requirement, decreases the motor’s oscillation, and gets the
better performance.