Tuning Guidelines for an Adaptive-Gain Parabolic Sliding Mode Filter - Shanhai Jin; Xiaodan Wang; Yonggao Jin; Xiaogang Xiong (Applied Sciences, 2017)
This paper quantitatively evaluates the performance of an adaptive-gain parabolic sliding mode filter (AG-PSMF), which is for removing noise in feedback control of mechatronic systems under different parameter values and noise intensities. The evaluation results show that, due to the nonlinearity of AG-PSMF, four performance measurements, i.e., transient time, overshoot magnitude, tracking error and computational time, vary widely under different conditions. Based on the evaluation results, the paper provides practical tuning guidelines for AG-PSMF to balance the tradeoff among the four measurements. The effectiveness of the guidelines is validated through numerical examples.