Sensor differential signals are widely used in many systems. The tracking differentiator\n(TD) is an effective method to obtain signal differentials. Differential calculation is noise-sensitive.\nThere is the characteristics of low-pass filter (LPF) in the TD to suppress the noise, but phase lag is\nintroduced. For LPF, fixed filtering parameters cannot achieve both noise suppression and phase\ncompensation lag compensation. We propose a fuzzy self-tuning tracking differentiator (FSTD)\ncapable of adaptively adjusting parameters, which uses the frequency information of the signal to\nachieve a trade-off between the phase lag and noise suppression capabilities. Based on the frequency\ninformation, the parameters of TD are self-tuning by a fuzzy method, which makes self-tuning\ndesigns more flexible. Simulations and experiments using motion measurement sensors show that\nthe proposed method has good filtering performance for low-frequency signals and improves tracking\nability for high-frequency signals compared to fixed-parameter differentiator.
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