Discrete-Time Sliding Mode Filter with Adaptive Gain

Abstract

Abstract:In feedback control of mechatronic systems, sensor signals are usually noisy and uncertain because of measurement errors and environmental disturbances. Such uncertainty and noise of feedback signals may cause instability of the controlled systems. This paper presents a new model-free discrete-time sliding mode filter for effectively removing noise by balancing the tradeoff between the filtering smoothness and the suppression of delay. The presented filter is an extension of a sliding mode filter (Jin et al. Real-time quadratic sliding mode filter for removing noise. Adv. Robot., 2012) by including an adaptive gain, of which value is determined in a similar way to that of a first-order adaptive windowing filter (Janabi-Sharifi et al. Discrete-time adaptive windowing for velocity estimation. IEEE Trans. Control Syst. Technol., 2000). The effectiveness of the presented filter is validated through numerical examples and experiments.

Discrete‐time sector based hands‐off control for nonlinear system

“…Theorem 3. The hands-off control law for a controllable discrete-time plant ensuring the monotonically decrease of the modified Lyapunov function (30) will be designed as…”

“…For that, a discrete‐time sector is designed by the involvement of comparison function results to accomplish a global asymptotic stability for discrete‐time nonlinear systems. Broadly, the control design for discrete nature of nonlinear plant is investigated in two ways, that is, discretization of continuous‐time control law and the direct design of control for the discrete‐time plant . Noteworthily, the second case is required to provide a specified velocity for a Lyapunov function to move to the interior of discrete‐time sector and subsequently decreases inside the sector without any control effort.…”

A SAKF-Based Composed Control Method for Improving Low-Speed Performance and Stability Accuracy of Opto-Electric Servomechanism

“…Janabi-Sharifi et al proposed a first-order adaptive windowing method (FOAW), which achieves a tradeoff between the noise suppression and the output rapidity by adaptively adjusting the differential step size of encoder data [7,8]. Jin et al proposed a parabolic sliding mode filter (PSMF) as well as the adaptive tuning methods for PSMF parameters [9][10][11][12][13][14]. Compared with the Butterworth filter, the PSMF has a larger amplitude-frequency gain as well as a smaller phase lag, so it can achieve a better speed estimation.…”

Tuning Guidelines for an Adaptive-Gain Parabolic Sliding Mode Filter

“…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. In that work, Jin et al stated that AG-PSMF effectively removes noise by balancing the tradeoff between the filtering smoothness and the suppression of delay [18].…”

“…After that, Jin et al [18] presented an adaptive-gain parabolic sliding mode filter, referred to as AG-PSMF, by extending PMSF. In that work, Jin et al stated that AG-PSMF effectively removes noise by balancing the tradeoff between the filtering smoothness and the suppression of delay [18]. However, due to the strong nonlinearity, theoretical evaluation and corresponding result-based parameter tuning guidelines remained as open problems for future study.…”