Multivariable H predictive control based on minimax predictor

Haipeng Zhao, Joseph Bentsman

Research output: Contribution to journalConference articlepeer-review


This paper presents a multi-input-multi-output H predictive controller design based on minimax predictor. Through the combination of the sequential spectral factorization and the coprime factorization, a k-step ahead MIMO H predictor is derived which is stable for the unstable noise model. This predictor minimizes the H norm of the power spectral density of the prediction error signal (and in fact flattens the spectrum), in contract to the standard quadratic predictor which minimizes the variance of the error signal. It is also shown that the minimax and quadratic predictors are equivalent for one-step ahead predictions. The H predictor and the internal model principle are embedded into the H optimization framework to address the disturbance rejection and the tracking problems, respectively. The inclusion of the minimax predictor into the H control algorithm introduces a tuning knob in the form of the prediction horizon, capable of setting a trade-off between the desired transient performance and the closed loop robustness.

Original languageEnglish (US)
Pages (from-to)3699-3705
Number of pages7
JournalProceedings of the IEEE Conference on Decision and Control
StatePublished - 1999
EventThe 38th IEEE Conference on Decision and Control (CDC) - Phoenix, AZ, USA
Duration: Dec 7 1999Dec 10 1999

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization


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