Design and Optimization of Intelligent PI Controllers (Fuzzy and Neuro-Fuzzy) for HVDC Transmission System

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.

Name thesis:degree_name

Master of Applied Science (MASc)

Discipline thesis:degree_discipline

Electrical and Computer Engineering

Grantor

University of Ontario Institute of Technology

Year dc:date.issued

2010

Author dc:creator

• Multani, Munish

Advisors dc:contributor.advisor

• Sood, Vijay K.
• Ren, Jing

• HVDC converter
• Fuzzy logic controller
• Membership function
• Neuro-fuzzy controller
• EMTP-RV

Language dc:language.iso

en

Handle dc:identifier.uri

https://hdl.handle.net/10155/103

OAI identifier oai:identifier

oai:ontariotechu.scholaris.ca:10155/103