{"id":21140283,"url":"https://github.com/d2hahn/second_order_time_domain_sys_id","last_synced_at":"2026-04-24T08:31:48.929Z","repository":{"id":256385323,"uuid":"855134756","full_name":"d2hahn/second_order_time_domain_sys_ID","owner":"d2hahn","description":"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.","archived":false,"fork":false,"pushed_at":"2024-11-11T21:06:19.000Z","size":36,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-14T13:12:27.141Z","etag":null,"topics":["control-systems","matlab","pressure-sensor","python","step-response","system-identification","time-domain"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/d2hahn.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-09-10T11:20:56.000Z","updated_at":"2024-11-11T21:06:23.000Z","dependencies_parsed_at":"2024-09-10T12:51:21.322Z","dependency_job_id":"c673c0b8-f9a4-410b-af07-8328e0c68aab","html_url":"https://github.com/d2hahn/second_order_time_domain_sys_ID","commit_stats":null,"previous_names":["d2hahn/second_order_time_domain_sys_id"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/d2hahn%2Fsecond_order_time_domain_sys_ID","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/d2hahn%2Fsecond_order_time_domain_sys_ID/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/d2hahn%2Fsecond_order_time_domain_sys_ID/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/d2hahn%2Fsecond_order_time_domain_sys_ID/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/d2hahn","download_url":"https://codeload.github.com/d2hahn/second_order_time_domain_sys_ID/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243581092,"owners_count":20314167,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["control-systems","matlab","pressure-sensor","python","step-response","system-identification","time-domain"],"created_at":"2024-11-20T07:13:59.515Z","updated_at":"2025-12-29T08:32:21.807Z","avatar_url":"https://github.com/d2hahn.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# second_order_time_domain_sys_ID\n\n\n## Summary\nPython 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.\n\n## Dependencies\n### Python\n1. functions.py\n2. matplotlib.pyplot\n3. matplotlib.SpanSelector\n4. numpy\n5. pandas\n6. scipy\n\n### MATLAB\n1. Control Systems Toolbox\n\n## Order of Use of Code\n1. csv_crop_prgrm.py (crop time-domain data to obtain portion of response that carries the dynamic chracteristics.)\n\n### Discrete-Time OLS Identification\n2. 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.)\n3. 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.)\n4. lsim_prgrm.m (Obtain simulation data of the response of the estimated model to the same input applied to the real system.)\n\n### Continuous-Time Identification\n2. second_order_approx_Tr_and_OS.py (Estimate natural frequency and damping ratio from response charactersitics obtained from cropped time-domain data.)\n3. 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.)\n4. lsim_prgrm.m (Obtain simulation data of the response of the estimated model to the same input applied to the real system.)\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fd2hahn%2Fsecond_order_time_domain_sys_id","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fd2hahn%2Fsecond_order_time_domain_sys_id","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fd2hahn%2Fsecond_order_time_domain_sys_id/lists"}