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Analysis and Correction of Ill-Conditioned Model in Multivariable Model Predictive Control

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Intelligent Robotics and Applications (ICIRA 2015)

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Abstract

The ill-conditioned model is a common problem in model predictive control. The model ill-conditioned can lead to control performance declining obviously from steady-state model of process in this paper. The direction of output movement is relevant to whether the model is ill-conditioned by simulation and analysis. Model mismatch also leads to model ill-conditioned becoming more serious. The geometry tools and SVD in linear algebra are used to analyze the essential reason of ill-conditioned model, and an offline strategy is proposed which can solve the ill-conditioned model problem together with existing online strategies. Finally, the simulations are used to prove the conclusions which presented in this paper are correct.

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Correspondence to Hao Pan .

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Pan, H., Yu, HB., Zou, T., Du, D. (2015). Analysis and Correction of Ill-Conditioned Model in Multivariable Model Predictive Control. In: Liu, H., Kubota, N., Zhu, X., Dillmann, R., Zhou, D. (eds) Intelligent Robotics and Applications. ICIRA 2015. Lecture Notes in Computer Science(), vol 9244. Springer, Cham. https://doi.org/10.1007/978-3-319-22879-2_56

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  • DOI: https://doi.org/10.1007/978-3-319-22879-2_56

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-22878-5

  • Online ISBN: 978-3-319-22879-2

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