Experimental studies in nonlinear discrete-time adaptive prediction and control

  • Authors:

  • R. Ordonez;J. T. Spooner;K. M. Passino

  • Affiliations:

  • Dept. of Electr. & Comput. Eng., Dayton Univ., OH;-;-

  • Venue:
  • IEEE Transactions on Fuzzy Systems
  • Year:
  • 2006

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Abstract

This paper presents implementation results using recently introduced discrete-time adaptive prediction and control techniques using online function approximators. We consider a process control experiment as our test bed, and develop a discrete-time adaptive predictor for liquid volume and a discrete-time adaptive controller for reference volume tracking. We use Takagi-Sugeno (TS) fuzzy systems as our function approximators, and for both prediction and control we investigate the use of a least-squares update of the fuzzy system's parameters