Generalized Predictive Control Parameter Adaptation Using a Fuzzy Logic Approach

dc.contributor.authorLloyd, John Williamen
dc.contributor.committeechairAhmadian, Mehdien
dc.contributor.committeememberTaheri, Saieden
dc.contributor.committeememberSouthward, Steve C.en
dc.contributor.committeememberSandu, Adrianen
dc.contributor.committeememberInman, Daniel J.en
dc.contributor.departmentMechanical Engineeringen
dc.date.accessioned2014-03-14T20:17:27Zen
dc.date.adate2011-11-09en
dc.date.available2014-03-14T20:17:27Zen
dc.date.issued2011-10-07en
dc.date.rdate2011-11-09en
dc.date.sdate2011-10-18en
dc.description.abstractA method to adapt the Generalized Predictive Control parameters to improve broadband disturbance rejection was developed and tested. The effect of the parameters on disturbance rejection has previously been poorly understood and a trial and error method was used to achieve adequate results. This dissertation provides insight on the effect of the parameters, as well as an adaptive tuning method to adjust them. The study begins by showing the effect of the four GPC parameters, the control and prediction horizons, control weighting &lambda , and order, on the disturbance rejection and control effort of a vibrating plate. It is shown that the effect of increases in the control and prediction horizon becomes negligible after a certain point. This occurs at nearly the same point for a variety of &lambda 's and orders, and hence they can be eliminated from the tuning space. The control effort and closed-loop disturbance rejection are shown to be highly dependant on &lambda and order, thereby becoming the parameters that need to be tuned. The behavior is categorized into various groups and further investigated. The pole and zero locations of the closed-loop system are examined to reveal how GPC gains control and how it can fail for non-minimum phase plants. A set of fuzzy logic modules is developed to adapt &lambda with order fixed, and conversely to adapt order with &lambda fixed. The effectiveness of the method is demonstrated in both numerical simulations and laboratory experiments.en
dc.description.degreePh. D.en
dc.identifier.otheretd-10182011-214341en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-10182011-214341/en
dc.identifier.urihttp://hdl.handle.net/10919/29306en
dc.publisherVirginia Techen
dc.relation.haspartLloyd_JW_D_2011.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectGPCen
dc.subjectgeneralized predictive controlen
dc.subjectactive controlen
dc.subjectadaptive controlen
dc.subjectfuzzy logicen
dc.subjectfuzzy logic adaptationen
dc.subjectvibration controlen
dc.subjectdisturbance rejectionen
dc.titleGeneralized Predictive Control Parameter Adaptation Using a Fuzzy Logic Approachen
dc.typeDissertationen
thesis.degree.disciplineMechanical Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.namePh. D.en

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Lloyd_JW_D_2011.pdf
Size:
4.99 MB
Format:
Adobe Portable Document Format