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dc.contributor.advisorDagher, Issamen_US
dc.contributor.authorHalby, Angie Alen_US
dc.contributor.authorBouty, Elie Elen_US
dc.descriptionIncludes bibliographical references (p.33-34).en_US
dc.descriptionSupervised by Dr. Issam Dagher.en_US
dc.description.abstractThe aim of this project is to tune a PID controller using artificial intelligence. The standard gain tuning of PID controllers such as Ziegler-Nichols, Coheen-Coon etc… tend to present big overshoots, and therefore artificial intelligence approach such as ant colony optimization and genetic algorithms are more adopted to enhance the results of standard techniques. However, due to computational efficiency, the main focus will be on the particle swarm optimization method (PSO). A comparison between PID and PSO versus PID and ZN (Ziegler-Nichols) will be represented where the results will show the advantage of PSO in PID tuning.en_US
dc.description.statementofresponsibilityby Angie Al Halby , Elie El Boutyen_US
dc.format.extentviii, 34 p. :ill., tables ;30 cmen_US
dc.rightsThis object is protected by copyright, and is made available here for research and educational purposes. Permission to reuse, publish, or reproduce the object beyond the personal and educational use exceptions must be obtained from the copyright holderen_US
dc.subject.lcshPID controllersen_US
dc.subject.lcshSwarm intelligenceen_US
dc.titleTuning a PID controller using particle swarm optimization (PSO)en_US
dc.contributor.departmentDepartment of Electrical Engineeringen_US
dc.contributor.facultyFaculty of Engineeringen_US
dc.contributor.institutionUniversity of Balamanden_US
dc.description.degreeMS in Electrical Engineeringen_US
Appears in Collections:UOB Theses and Projects
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