Online Condition Monitoring of Electrolytic Capacitors in DC-DC Interleaved Boost Converters, Adopting a Model-Free Predictive Controller

2021 ◽  
Author(s):  
Khaled Laadjal ◽  
Fernando Bento ◽  
Imed Jlassi ◽  
A. J. Marques Cardoso
Keyword(s):  
Condition Monitoring ◽  
Boost Converters ◽  
Electrolytic Capacitors ◽  
Model Free ◽  
Predictive Controller

Condition Monitoring of Electrolytic Capacitors in Boost Converters by Magnetic Sensors

2019 ◽  
Vol 19 (22) ◽  
pp. 10393-10402 ◽  
Author(s):  
Wenchao Miao ◽  
Xuyang Liu ◽  
K.H. Lam ◽  
Philip W. T. Pong
Keyword(s):  
Condition Monitoring ◽  
Magnetic Sensors ◽  
Boost Converters ◽  
Electrolytic Capacitors

Fault-Tolerant Model-Free Predictive Controller for Multilevel Cascaded H-bridge Inverters with Faulty Cells

2021 ◽  
pp. 1-1
Author(s):  
Paul Gistain Ipoum-Ngome ◽  
Rodolfo C.C. Flesch ◽  
Daniel Legrand Mon-Nzongo ◽  
Tang Jinquan ◽  
Jin Tao ◽  
...  
Keyword(s):  
Fault Tolerant ◽  
Model Free ◽  
Predictive Controller

Condition Monitoring of DC-Link Electrolytic Capacitors in Adjustable-Speed Drives

2008 ◽  
Vol 44 (5) ◽  
pp. 1606-1613 ◽  
Author(s):  
Kwang-Woon Lee ◽  
Myungchul Kim ◽  
Jangho Yoon ◽  
Sang Bin Lee ◽  
Ji-Yoon Yoo
Keyword(s):  
Condition Monitoring ◽  
Adjustable Speed Drives ◽  
Electrolytic Capacitors ◽  
Adjustable Speed

Model-free condition monitoring with confidence

2019 ◽  
Vol 32 (4-5) ◽  
pp. 466-481 ◽  
Author(s):  
M. Götzinger ◽  
N. TaheriNejad ◽  
H. A. Kholerdi ◽  
A. Jantsch ◽  
E. Willegger ◽  
...  
Keyword(s):  
Condition Monitoring ◽  
Free Condition ◽  
Model Free

An Online and Noninvasive Technique for the Condition Monitoring of Capacitors in Boost Converters

2010 ◽  
Vol 59 (8) ◽  
pp. 2134-2143 ◽  
Author(s):  
G M Buiatti ◽  
J A Martín-Ramos ◽  
C H R García ◽  
A M R Amaral ◽  
A J M Cardoso
Keyword(s):  
Condition Monitoring ◽  
Noninvasive Technique ◽  
Boost Converters

scholarly journals Broad Learning Aided Model Predictive Control With Application to Continuous Stirred Tank Heater

2021 ◽  
Vol 2 ◽  
Author(s):  
Mo Tao ◽  
Tianyi Gao ◽  
Xianling Li ◽  
Kuan Li
Keyword(s):  
Model Predictive Control ◽  
Predictive Model ◽  
Predictive Control ◽  
Learning Algorithm ◽  
Stirred Tank ◽  
Process Data ◽  
Computational Load ◽  
Model Free ◽  
Predictive Controller ◽  
Continuous Stirred Tank

This paper presents a data-driven predictive controller based on the broad learning algorithm without any prior knowledge of the system model. The predictive controller is realized by regressing the predictive model using online process data and the incremental broad learning algorithm. The proposed model predictive control (MPC) approach requires less online computational load compared to other neural network based MPC approaches. More importantly, the precision of the predictive model is enhanced with reduced computational load by operating an appropriate approximation of the predictive model. The approximation is proved to have no influence on the convergence of the predictive control algorithm. Compared with the partial form dynamic linearization aided model free control (PFDL-MFC), the control performance of the proposed predictive controller is illustrated through the continuous stirred tank heater (CSTH) benchmark.

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