Data‐Driven Performance Monitoring for Model Predictive Control Using a mahalanobis distance based overall index-Reference-Cited by-同舟云学术

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

Published:2018-06-04 Issue:2 Volume:21 Page:891-907
ISSN:1561-8625
Container-title:Asian Journal of Control
language:en
Short-container-title:Asian Journal of Control

Author:

Xu Yanting¹,Zhang Guangming¹,Li Ning¹^ORCID,Zhang Jing¹,Li Shaoyuan¹^ORCID,Wang Lu¹

Affiliation:

1. Department of Automation Shanghai Jiao Tong University Shanghai 200240 China

Funder

the National Nature Science Foundation of China

the National Basic Research Program of China

the National High Technology R&D Program of China

Publisher

Wiley

Subject

Control and Systems Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/asjc.1782

Reference48 articles.

1. Model predictive control to mitigate chatters in milling processes with input constraints

2. A Novel Multi-Step Model Predictive Control for Multi-Input Systems

3. Performance monitoring of model-predictive controllers via model residual assessment

4. Bayesian Learning-Based Model-Predictive Vibration Control for Thin-Walled Workpiece Machining Processes

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1. Control performance monitoring of chemical industrial process based on model residual;2024 39th Youth Academic Annual Conference of Chinese Association of Automation (YAC);2024-06-07

2. Data-driven control loop performance evaluation of electromagnetic levitation systems;2020 Chinese Automation Congress (CAC);2020-11-06

3. Robust output feedback predictive controller with adaptive invariant tubes and observer gains;International Journal of Dynamics and Control;2020-08-24

4. Performance Assessment of Predictive Control—A Survey;Algorithms;2020-04-17

5. An Enhanced Method to Assess MPC Performance Based on Multi-Step Slow Feature Analysis;Energies;2019-10-08

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