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A Simplified Fuzzy Relational Structure for Adaptive Predictive Control

  • J. Valente de Oliveira
  • J. M. Lemos
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 16)

Abstract

Model based predictive controllers have a number of appealing features such as:
  • The ability to take into account the impact of the current control action on the future process state. This is a useful when dealing with non-minimum phase behaviors (e.g., to stablize plants whose open-loop response to a positive input step results first in a decrement of the output and only afterwards, in an increment), unknown or partially unknown dynamics.

  • The ability to accomodate knowledge about future requirements on the plant state represented in terms of a pre-defined tracking reference signal.

  • Effectiveness of control even when the predictor is a coarse approximator of the plant dynamics

  • The ability to deal with multiple objectives and constraints, e.g., on the manipulated variable.

Keywords

Membership Function Fuzzy System Fuzzy Rule Composition Operator Recursive Little Square 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • J. Valente de Oliveira
    • 1
  • J. M. Lemos
    • 2
  1. 1.Dept. Mathematics and Computer ScienceUBICovilhãPortugal
  2. 2.Research Group on Control of Dynamic SystemsINESCLisboaPortugal

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