Bilinear discrete-time modeling for enhanced stability prediction and digital control design

2003 ◽  
Vol 18 (1) ◽  
pp. 381-389 ◽  
Author(s):  
V. Rajasekaran ◽  
Jian Sun ◽  
B.S. Heck
Keyword(s):  
Discrete Time ◽  
Digital Control ◽  
Control Design ◽  
Stability Prediction ◽  
Time Modeling ◽  
Discrete Time Modeling ◽  
Enhanced Stability

Discrete-time modeling of Li-ion batteries with electrochemical overpotentials including diffusion

2021 ◽  
Vol 500 ◽  
pp. 229991
Author(s):  
Alan G. Li ◽  
Karthik Mayilvahanan ◽  
Alan C. West ◽  
Matthias Preindl
Keyword(s):  
Discrete Time ◽  
Li Ion Batteries ◽  
Time Modeling ◽  
Li Ion ◽  
Discrete Time Modeling

scholarly journals Discrete-time modeling of Hamiltonian systems

2015 ◽  
Vol 23 ◽  
pp. 149-170 ◽  
Author(s):  
Yaprak YALÇIN ◽  
Leyla GÖREN SÜMER ◽  
Salman KURTULAN
Keyword(s):  
Hamiltonian Systems ◽  
Discrete Time ◽  
Time Modeling ◽  
Discrete Time Modeling

DEBUGGING PROCESS-ORIENTED DISCRETE SOFTWARE RELIABILITY MODELING

2009 ◽  
Vol 16 (04) ◽  
pp. 357-370 ◽  
Author(s):  
SHINJI INOUE ◽  
NAOKI IWAMOTO ◽  
SHIGERU YAMADA
Keyword(s):  
Discrete Time ◽  
Software Reliability ◽  
Goodness Of Fit ◽  
Growth Models ◽  
Reliability Growth ◽  
Reliability Modeling ◽  
New Approach ◽  
Time Modeling ◽  
Software Reliability Growth ◽  
Discrete Time Modeling

This paper discusses an new approach for discrete-time software reliability growth modeling based on an discrete-time infinite server queueing model, which describes a debugging process in a testing phase. Our approach enables us to develop discrete-time software reliability growth models (SRGMs) which could not be developed under conventional discrete-time modeling approaches. This paper also discuss goodness-of-fit comparisons of our discrete-time SRGMs with conventional continuous-time SRGMs in terms of the criterion of the mean squared errors, and show numerical examples for software reliability analysis of our models by using actual data.

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