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Predictive Self-Tuning Control by Parameter Bounding and Worst-Case Design

  • S. M. Veres
  • J. P. Norton

Abstract

The computation of bounds on the parameters of a plant model allows worst-case control synthesis, taking account of the uncertainty in the model. This chapter introduces such a control scheme: predictive bounding control. The scheme contrasts with existing self-tuning control methods which base control synthesis on a nominal plant model. Parameter bounding also permits detection of abrupt plant changes, and adaptive tracking of time-varying plant characteristics by suitable choice of bounds on plant-model output error and plant-parameter increments. Estimation and control are closely integrated, and the control computation can compromise between reducing the model uncertainty and reducing predicted output error. Simulation examples show the excellent performance of predictive bounding control.

Keywords

Control Input Control Output Output Error Disturbance Signal Parameter Bound 
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 Science+Business Media New York 1996

Authors and Affiliations

  • S. M. Veres
    • 1
  • J. P. Norton
    • 1
  1. 1.School of Electronic and Electrical EngineeringUniversity of BirminghamEdgbaston, BirminghamUK

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