https://github.com/d2hahn/second_order_time_domain_sys_id

Python and MATLAB codebase for performing second-order system identification from time-domain data of a systems dynamic response to a decreasing step input function.
https://github.com/d2hahn/second_order_time_domain_sys_id

control-systems matlab pressure-sensor python step-response system-identification time-domain

Last synced: 16 days ago
JSON representation

Python and MATLAB codebase for performing second-order system identification from time-domain data of a systems dynamic response to a decreasing step input function.

• Host: GitHub
• URL: https://github.com/d2hahn/second_order_time_domain_sys_id
• Owner: d2hahn
• License: mit
• Created: 2024-09-10T11:20:56.000Z (5 months ago)
• Default Branch: main
• Last Pushed: 2024-11-11T21:06:19.000Z (3 months ago)
• Last Synced: 2025-01-21T06:45:00.754Z (16 days ago)
• Topics: control-systems, matlab, pressure-sensor, python, step-response, system-identification, time-domain
• Language: Python
• Homepage:
• Size: 35.2 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# second_order_time_domain_sys_ID

## Summary

Python and MATLAB codebase for performing second-order system identification from time-domain data of a systems dynamic response to a decreasing step input function. Both discrete and continuous time estimation methods are available. Uncertainties given at the 95% confidence level. Code was originally developed to characterize dynamics of pressure sensor apparatuses through decreasing step response testing.

## Dependencies

### Python

1. functions.py

2. matplotlib.pyplot

3. matplotlib.SpanSelector

4. numpy

5. pandas

6. scipy

### MATLAB

1. Control Systems Toolbox

## Order of Use of Code

1. csv_crop_prgrm.py (crop time-domain data to obtain portion of response that carries the dynamic chracteristics.)

### Discrete-Time OLS Identification

2. second_order_approx_w_LS.py or 2_order_LS_w_2_zero.py (Perform OLS fit of discrete-time 2nd order model to cropped time-domain data considering either a single zero or two zeroes, outputs estimated parameters.)

3. ct_param_est_from_dt_param_est.m or ct_param_est_from_dt_param_est_2_zeroes.m (Convert discrete-time transfer function estimated in 2. to continuous-time, also obtain step response data of simulated transfer function for comparison to experimental data. Use for either one or two zeroes.)

4. lsim_prgrm.m (Obtain simulation data of the response of the estimated model to the same input applied to the real system.)

### Continuous-Time Identification

2. second_order_approx_Tr_and_OS.py (Estimate natural frequency and damping ratio from response charactersitics obtained from cropped time-domain data.)

3. second_order_response_from_dr_and_wn.m (Calculating general second-order TF parameters from estimated nat. freq and damping ratio. Also obtaining frequency response data.)

4. lsim_prgrm.m (Obtain simulation data of the response of the estimated model to the same input applied to the real system.)