Developing a Hybrid Stochastic and Deterministic Alpha, Beta, Gamma Filter with SNR for Sensorless Control Using Propagation of Uncertainties with a Two Phase Stepper Motor as an Example
Abstract
Sensorless control of systems requires precise measurements for feedback in recursive algorithms however measurement noise and process noise injects error into the signal where the error can cascade and cause the system to become uncontrollable. Sensorless control using the Kalman filter requires significant computation time that can degrade the processor performance and instigate timing issues with the processor while the alpha, beta, gamma filter requires less computational resources; requires tuning; and less accurate. In this paper, one reformulates the alpha, beta, and gamma gains to develop an alpha, beta and gamma filter with signal to noise ratio using propagation of uncertainties in order to conserve computation time and increase the performance and accuracy of the alpha, beta, gamma filter. In addition, the system is modeled with two plants for the purposes of tuning the filter to compensate for the environmental effects, noise, other perturbations such as the squared errors and others.
Document Details
- Document Type
- Technical Report
- Publication Date
- Aug 17, 2020
- Accession Number
- AD1106282
Entities
People
- Julian Mertens