Data‐Driven Performance Monitoring for Model Predictive Control Using a mahalanobis distance based overall index

DOI10.1002/asjc.1782zbMath1422.93070OpenAlexW2805984854MaRDI QIDQ5194906

Lu Wang, Guang-Ming Zhang, Jing Zhang, Yanting Xu, Shao-Yuan Li, Ning Li

Publication date: 17 September 2019

Published in: Asian Journal of Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/asjc.1782

zbMATH Keywords

performance monitoringmodel predictive control (MPC)data-drivencontroller performance monitoring (CPM)Mahalanobis distance based index (MDBI)

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Cites Work

• Multi-model predictive control based on the Takagi-Sugeno fuzzy models: a case study
• Multiple model predictive control for large envelope flight of hypersonic vehicle systems
• Principal component analysis.
• Tube MPC scheme based on robust control invariant set with application to Lipschitz nonlinear systems
• An efficient model predictive controller with pole placement
• A Novel Multi-Step Model Predictive Control for Multi-Input Systems
• Prediction Error Based Performance Monitoring, Degradation Diagnosis and Remedies in Offset-Free MPC: Theory and Applications
• The Detection of Errors in Multivariate Data Using Principal Components
• Some Theorems on Quadratic Forms Applied in the Study of Analysis of Variance Problems, I. Effect of Inequality of Variance in the One-Way Classification

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