{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/124683"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/124683","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Automation of power adaptation for electrosurgery","abstract":"Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2026-05-01","abstract_html":"Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2026-05-01","abstract_has_math":false,"creators":["Prakash, Praveen"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Mechanical Engineering","degree_department":null,"school":null,"contributors":["Bentsman, Joseph"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2024,"date_issued":"2024-05","date_published":"2024-05","updated_at":"2026-07-22T22:25:02Z","subjects":["Electrosurgery","Power Adaptation","Power Tracking","Control","Cutting","Coagulation","Fpga","Gpc","Generalized Predictive Control"],"languages":["en","eng"],"rights":["Copyright 2024 Praveen Prakash"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/124683","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Bentsman, Joseph"]},{"key":"dc:creator","label":"Author","values":["Prakash, Praveen"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2024-05","2024-05-01"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Mechanical Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Electrosurgery","Power Adaptation","Power Tracking","Control","Cutting","Coagulation","Fpga","Gpc","Generalized Predictive Control"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2024 Praveen Prakash"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/124683"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2026-05-01","The student, Praveen Prakash, accepted the attached license on 2024-04-22 at 14:19.","The student, Praveen Prakash, submitted this Thesis for approval on 2024-04-22 at 15:39.","This Thesis was approved for publication on 2024-05-01 at 15:58.","DSpace SAF Submission Ingestion Package generated from Vireo submission #20546 on 2024-09-16 at 00:49:54","Well-selected power with accurate delivery is of importance in electrosurgery to generate proper temperature at the cutting site, and thus, reduce undesired collateral tissue damages. The power reference setpoint is determined either based on temperature or impedance. Bao et al. [1] present PI controller for power adaptation using commercially low-cost industrial-scale digital signal processor (DSP). In this thesis different control algorithms for cutting and coagulation modes for power tracking are explored. The plant models are based on data obtained from electrosurgery experiments on live pigs. The controllers explored are: Linear Quadratic Regulator (LQR), General Predictive Control (GPC), and Direct methods. In LQR and GPC the reference current is updated in real-time to ensure power tracking using linear models. Moreover, the moving window approach is used to achieve faster adaptation. Further to assess the non-linearity in the plant model, wavelet based Non-linear Autoregressive model with Exogenous inputs are derived. To sample and precisely reconstruct signals of hundreds of kilohertz it is proposed to use Xilinx field-programmable gate array (FPGA). The implementation steps and results from these analyses are presented."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Automation of power adaptation for electrosurgery"]}]}],"canonical_facts":{"dc:contributor":["Bentsman, Joseph"],"dc:creator":["Prakash, Praveen"],"dc:date":["2024-05","2024-05-01"],"dc:description":["Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2026-05-01","The student, Praveen Prakash, accepted the attached license on 2024-04-22 at 14:19.","The student, Praveen Prakash, submitted this Thesis for approval on 2024-04-22 at 15:39.","This Thesis was approved for publication on 2024-05-01 at 15:58.","DSpace SAF Submission Ingestion Package generated from Vireo submission #20546 on 2024-09-16 at 00:49:54","Well-selected power with accurate delivery is of importance in electrosurgery to generate proper temperature at the cutting site, and thus, reduce undesired collateral tissue damages. The power reference setpoint is determined either based on temperature or impedance. Bao et al. [1] present PI controller for power adaptation using commercially low-cost industrial-scale digital signal processor (DSP). In this thesis different control algorithms for cutting and coagulation modes for power tracking are explored. The plant models are based on data obtained from electrosurgery experiments on live pigs. The controllers explored are: Linear Quadratic Regulator (LQR), General Predictive Control (GPC), and Direct methods. In LQR and GPC the reference current is updated in real-time to ensure power tracking using linear models. Moreover, the moving window approach is used to achieve faster adaptation. Further to assess the non-linearity in the plant model, wavelet based Non-linear Autoregressive model with Exogenous inputs are derived. To sample and precisely reconstruct signals of hundreds of kilohertz it is proposed to use Xilinx field-programmable gate array (FPGA). The implementation steps and results from these analyses are presented."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/124683"],"dc:language":["en","eng"],"dc:rights":["Copyright 2024 Praveen Prakash"],"dc:subject":["Electrosurgery","Power Adaptation","Power Tracking","Control","Cutting","Coagulation","Fpga","Gpc","Generalized Predictive Control"],"dc:title":["Automation of power adaptation for electrosurgery"],"dc:type":["text"],"thesis:degree_discipline":["Mechanical Engineering"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:02Z"}