A First-Order Differentiator with First-Order Sliding Mode Filtering

This paper proposes a sliding mode differentiator for estimating the first-order derivatives of noisy signals. The proposed differentiator can be seen as a version of Slotine at al.'s sliding mode observer extended with additional non-Lipschitzness. It behaves exactly as a first-order low-pass filter in the sliding mode and is globally convergent. Its discrete-time implementation is based on the implicit (backward) Euler discretization, which does not result in chattering. The differentiator is validated through some numerical examples. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.