{"id":{"repo_id":"uoit","oai_identifier":"oai:ontariotechu.scholaris.ca:10155/103"},"canonical_url":"https://search.dev.ndltd.org/etd/uoit/oai:ontariotechu.scholaris.ca:10155/103","repository":{"repo_id":"uoit","name":"Ontario Institute of Technology","base_url":"https://ontariotechu.scholaris.ca/server/oai/request"},"display":{"title":"Design and Optimization of Intelligent PI Controllers (Fuzzy and Neuro-Fuzzy) for HVDC Transmission System","abstract":"This thesis deals with enhancing the performance of Fuzzy Logic (FL) based PI controllers for High Voltage Direct Current Transmission Systems (HVDC) by optimizing the key parameters i.e. membership functions (MFs) and fuzzy rule base in the controllers design. In the first part of the thesis, an adaptive Fuzzy PI controller is designed and the effect of various MF shapes, widths and distribution on the performance of a FL controlled HVDC system under different system conditions is studied with the aim of selecting a MF which minimizes the total control error. Simulated results show that the shape, width and distribution of a MF influences the performance of the FL controller and concludes that nonlinear MFs (i.e. Gaussian) offer a more better choice than linear (i.e. Triangular) MFs as the former provides a smoother transition at the switching points and thus propose a better controller. In the second part of the thesis, a Neuro-Fuzzy (NF) controller to update the fuzzy rule base with changing system conditions is proposed, which in turn adjusts the PI gains of a conventional PI controller. Results from simulations illustrate the potential of the proposed control scheme as the NF controller successfully adapts to different system conditions and is able to minimize the total current error.","abstract_html":"This thesis deals with enhancing the performance of Fuzzy Logic (FL) based PI controllers for High Voltage Direct Current Transmission Systems (HVDC) by optimizing the key parameters i.e. membership functions (MFs) and fuzzy rule base in the controllers design. In the first part of the thesis, an adaptive Fuzzy PI controller is designed and the effect of various MF shapes, widths and distribution on the performance of a FL controlled HVDC system under different system conditions is studied with the aim of selecting a MF which minimizes the total control error. Simulated results show that the shape, width and distribution of a MF influences the performance of the FL controller and concludes that nonlinear MFs (i.e. Gaussian) offer a more better choice than linear (i.e. Triangular) MFs as the former provides a smoother transition at the switching points and thus propose a better controller. In the second part of the thesis, a Neuro-Fuzzy (NF) controller to update the fuzzy rule base with changing system conditions is proposed, which in turn adjusts the PI gains of a conventional PI controller. Results from simulations illustrate the potential of the proposed control scheme as the NF controller successfully adapts to different system conditions and is able to minimize the total current error.","abstract_has_math":false,"creators":["Multani, Munish"],"institution":"University of Ontario Institute of Technology","degree_name":"Master of Applied Science (MASc)","degree_level":null,"degree_discipline":"Electrical and Computer Engineering","degree_department":null,"school":null,"contributors":[],"advisors":["Sood, Vijay K.","Ren, Jing"],"committee_chairs":[],"committee_members":[],"year":2010,"date_issued":"2010-08-01","date_published":"2010-08-01","updated_at":"2026-07-24T05:35:32Z","subjects":["HVDC converter","Fuzzy logic controller","Membership function","Neuro-fuzzy controller","EMTP-RV"],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/10155/103","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Sood, Vijay K.","Ren, Jing"]},{"key":"dc:creator","label":"Author","values":["Multani, Munish"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2010-10-13T20:29:55Z","2022-03-29T14:52:54Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2010-10-13T20:29:55Z","2022-03-29T14:52:54Z"]},{"key":"dc:date.issued","label":"Date","values":["2010-08-01"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical and Computer Engineering"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Applied Science (MASc)"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Ontario Institute of Technology"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["HVDC converter","Fuzzy logic controller","Membership function","Neuro-fuzzy controller","EMTP-RV"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/10155/103"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This thesis deals with enhancing the performance of Fuzzy Logic (FL) based PI controllers for High Voltage Direct Current Transmission Systems (HVDC) by optimizing the key parameters i.e. membership functions (MFs) and fuzzy rule base in the controllers design. In the first part of the thesis, an adaptive Fuzzy PI controller is designed and the effect of various MF shapes, widths and distribution on the performance of a FL controlled HVDC system under different system conditions is studied with the aim of selecting a MF which minimizes the total control error. Simulated results show that the shape, width and distribution of a MF influences the performance of the FL controller and concludes that nonlinear MFs (i.e. Gaussian) offer a more better choice than linear (i.e. Triangular) MFs as the former provides a smoother transition at the switching points and thus propose a better controller. In the second part of the thesis, a Neuro-Fuzzy (NF) controller to update the fuzzy rule base with changing system conditions is proposed, which in turn adjusts the PI gains of a conventional PI controller. Results from simulations illustrate the potential of the proposed control scheme as the NF controller successfully adapts to different system conditions and is able to minimize the total current error."]},{"key":"dc:title","label":"Title","values":["Design and Optimization of Intelligent PI Controllers (Fuzzy and Neuro-Fuzzy) for HVDC Transmission System"]}]}],"canonical_facts":{"dc:contributor.advisor":["Sood, Vijay K.","Ren, Jing"],"dc:creator":["Multani, Munish"],"dc:date.accessioned":["2010-10-13T20:29:55Z","2022-03-29T14:52:54Z"],"dc:date.available":["2010-10-13T20:29:55Z","2022-03-29T14:52:54Z"],"dc:date.issued":["2010-08-01"],"dc:description.abstract":["This thesis deals with enhancing the performance of Fuzzy Logic (FL) based PI controllers for High Voltage Direct Current Transmission Systems (HVDC) by optimizing the key parameters i.e. membership functions (MFs) and fuzzy rule base in the controllers design. In the first part of the thesis, an adaptive Fuzzy PI controller is designed and the effect of various MF shapes, widths and distribution on the performance of a FL controlled HVDC system under different system conditions is studied with the aim of selecting a MF which minimizes the total control error. Simulated results show that the shape, width and distribution of a MF influences the performance of the FL controller and concludes that nonlinear MFs (i.e. Gaussian) offer a more better choice than linear (i.e. Triangular) MFs as the former provides a smoother transition at the switching points and thus propose a better controller. In the second part of the thesis, a Neuro-Fuzzy (NF) controller to update the fuzzy rule base with changing system conditions is proposed, which in turn adjusts the PI gains of a conventional PI controller. Results from simulations illustrate the potential of the proposed control scheme as the NF controller successfully adapts to different system conditions and is able to minimize the total current error."],"dc:identifier.uri":["https://hdl.handle.net/10155/103"],"dc:language.iso":["en"],"dc:subject":["HVDC converter","Fuzzy logic controller","Membership function","Neuro-fuzzy controller","EMTP-RV"],"dc:title":["Design and Optimization of Intelligent PI Controllers (Fuzzy and Neuro-Fuzzy) for HVDC Transmission System"],"dc:type":["Thesis"],"thesis:degree_discipline":["Electrical and Computer Engineering"],"thesis:degree_name":["Master of Applied Science (MASc)"],"thesis:institution_name":["University of Ontario Institute of Technology"]},"updated_at":"2026-07-24T05:35:32Z"}