给出了基于卡尔曼滤波的测速方法，并利用电流、角速度等参数估算出加速度，作为卡尔曼滤波的控制输入。仿真了该方法的稳态和动态性能，并与其他滤波方法做了对比；将该方法应用于某伺服系统，测试并分析了系统的0.1°/s阶跃响应、频域特性及参数摄动对滤波性能的影响。结果表明，该方法减小了低速时的测速误差和相位延时，扩展了速度环带宽，并且对参数变化不敏感，具有较强的鲁棒性。%A velocity estimation method using kalman filter was given. Acceleration was considered as control input of kalman filter, and was estimated by motor current and velocity. The steady and dynamic performance had been simulated, the results of this method was compared with other filtering methods. The method was applied to a servo system. Some key performance indicators had been measured and analyzed, such as 0. 1 °/ s step response, frequency domain characteristics and the influence of parameter perturbation. Results showed that kalman filter based on the kinematics could reduce velocity estimation error and phase lag, expanded speed loop bandwidth, and was not sensitive to parameters perturbation, which has strong robustness.
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