Parameter Selection Guidelines for a Parabolic Sliding Mode Filter Based on Frequency and Time Domain Characteristics

Abstract

This paper presents the results of quantitative performance evaluation of an authors' new parabolic sliding mode filter, which is for removing noise from signals in robotics and mechatronics applications, based on the frequency and time domain characteristics. Based on the evaluation results, the paper presents selection guidelines of two parameters of the filter. The evaluation results show that, in the frequency domain, the noise removing capability of the filter is almost the same as that of the second-order Butterworth low-pass filter (2-LPF), but its phase lag is smaller (maximum 150 degree) than that of 2-LPF (maximum 180 degree). Moreover, the filter produces smaller phase lag than a conventional parabolic sliding mode filter with appropriate selection of the parameters. In the time domain, the filter produces smaller overshoot than 2-LPF and the conventional one, while maintaining short transient time, by using an appropriately selected parameter. The presented parameter selection guidelines state that the values of the parameters should be chosen according to some estimated characteristics of the input and some desired characteristics of the output. The effectiveness of the filter and the presented guidelines is validated through numerical examples and their application to a closed-loop, force control of a robot manipulator.

Discrete-Time Sliding Mode Filter with Adaptive Gain

“…In Ref. [21], it is reported that the noise removing capability of PSMF is almost the same as that of 2-LPF, but its phase lag is smaller than that of 2-LPF. Moreover, compared with the filter [12,13], PSMF is less prone to overshoot, and it produces smaller phase lag.…”

“…Moreover, compared with the filter [12,13], PSMF is less prone to overshoot, and it produces smaller phase lag. The effectiveness of PSMF has been experimentally validated [21,22].…”

Tuning Guidelines for an Adaptive-Gain Parabolic Sliding Mode Filter

“…It is reported [16,17] that the noise removing capability of PSMF is almost the same as that of second-order Butterworth low-pass filter (2-LPF), but PSMF produces smaller phase lag than 2-LPF does. In addition, compared with the filter in [1,2], PSMF produces smaller phase lag , and it is less prone to overshooting.…”

“…In addition, compared with the filter in [1,2], PSMF produces smaller phase lag , and it is less prone to overshooting. The effectiveness of PSMF has been experimentally validated [16,17]. However, due to the fixed acceleration gain F, the output of PSMF cannot follow an input in which the acceleration exceeds that of PSMF, whereas the output becomes sensitive to the noise contained in the input of which acceleration is far below that of PSMF.…”

“…It is reported [16,17] that PSMF is advantageous over the filter referred to in [1,2] and linear filters because it is less prone to overshooting and produces smaller phase lag. After that, Jin et al [18] presented an adaptive-gain parabolic sliding mode filter, referred to as AG-PSMF, by extending PMSF.…”