Title page for ETD etd-10182011-214341

Type of Document Dissertation
Author Lloyd, John William
URN etd-10182011-214341
Title Generalized Predictive Control Parameter Adaptation Using a Fuzzy Logic Approach
Degree PhD
Department Mechanical Engineering
Advisory Committee
Advisor Name Title
Ahmadian, Mehdi Committee Chair
Inman, Daniel J. Committee Member
Sandu, Adrian Committee Member
Southward, Steve C. Committee Member
Taheri, Saied Committee Member
  • GPC
  • generalized predictive control
  • active control
  • adaptive control
  • fuzzy logic
  • fuzzy logic adaptation
  • vibration control
  • disturbance rejection
Date of Defense 2011-10-07
Availability unrestricted
A 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.

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