Adaptive differentiating filter: case study of PID feedback control
For control engineers, this filter offers a practical solution for accurate velocity estimation in mechatronic systems with improved noise rejection and responsiveness.
The paper introduces an adaptive causal discrete-time filter for derivative estimation that balances noise sensitivity and bandwidth, and demonstrates its superior performance in a PID feedback control case study compared to standard and robust differentiators.
This paper presents an adaptive causal discrete-time filter for derivative estimation, exemplified by its use in estimating relative velocity in a mechatronic application. The filter is based on a constrained least squares estimator with window adaptation. It demonstrates low sensitivity to low-amplitude measurement noise, while preserving a wide bandwidth for large-amplitude changes in the process signal. Favorable performance properties of the filter are discussed and demonstrated in a practical case study of PID feedback controller and compared experimentally to a standard linear low-pass filter-based differentiator and a robust sliding-mode based homogeneous differentiator.