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Multiple Model Predictive Control: A State Estimation based Approach | IEEE Conference Publication | IEEE Xplore

Multiple Model Predictive Control: A State Estimation based Approach


Abstract:

An augmented state formulation for multiple model predictive control (MMPC) is developed to improve the regulation of nonlinear and uncertain process systems. By augmenti...Show More

Abstract:

An augmented state formulation for multiple model predictive control (MMPC) is developed to improve the regulation of nonlinear and uncertain process systems. By augmenting disturbances as states that are estimated using a Kalman filter, improved disturbance rejection is achieved compared to an additive output disturbance assumption. The approach is applied to a quadratic tank example, which has challenging dynamic behavior, switching from minimum phase to nonminimum phase behavior as the operating conditions are changed.
Date of Conference: 09-13 July 2007
Date Added to IEEE Xplore: 30 July 2007
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Conference Location: New York, NY, USA

References

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