riccati difference equation
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2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Liang Zeng

PurposeTo develop the theory and application of the grey prediction model, this investigation constructs a novel discrete grey Riccati model termed DGRM(1,1).Design/methodology/approachBy examining a special kind of Riccati difference equation and the structure of the conventional discrete grey model (DGM), we advance a novel DGRM, and the model's prediction effect is evaluated by two numerical examples and an application case and compared with that of other conventional grey models.FindingsThe average relative simulation error of DGRM(1,1) does not change if the model is built after the original sequence has been transformed by a multiplier, and the new model is suitable to predict monotonically increasing, monotonically decreasing and unimodal sequences.Practical implicationsDGRM(1,1) is utilized to forecast the development cost of a small plane owned by the Aviation Industry Corporation of China (AVIC) with an original data sequence from 2006 to 2013. The outcomes indicate that DGRM(1,1) exhibits high precision and potential in development cost prediction.Originality/valueCombining the Riccati difference equation with the conventional DGM, the author advances a new grey model that is suitable to predict three kinds of data series with different changing trends.


Author(s):  
M. Sumathy ◽  
M. Maria Susai Manuel ◽  
Adem Kılıçman ◽  
Jesintha Mary

In this paper, initially a mathematical model is formulated for transient frequency of power system considering time delays which occur while transmitting the control signals in open communication infrastructure. Time delay negligence in a power system leads to improper measurement of frequency variation in power system. The study of impact of time delays on the stability of power system is performed by estimating the decay rate of frequency wave form using Kalman Filter (KF). In power system, there is a possibility of multiple time delays. This paper also focusses on developing Interacting Multiple Model (IMM) Algorithm with multiple model space using Kalman Filter (KF) as state estimator tool. The multiple time delays in power system is considered as multiple model space. The result shows that KF provides better estimate of correct model for a particular input-set. The qualitative properties of Riccati difference equation (RDE) in terms of state error covariance of IMMKF are also analyzed and presented.


Author(s):  
M. Sumathy ◽  
Adem Kılıçman ◽  
M. Maria Susai Manuel ◽  
Jesintha Mary

In this paper, initially a mathematical model is formulated for transient frequency of power system considering time delays which occur while transmitting the control signals in open communication infrastructure. Time delay negligence in a power system leads to improper measurement of frequency variation in power system. The study of impact of time delays on the stability of power system is performed by estimating the decay rate of frequency wave form using Kalman Filter (KF). In power system, there is a possibility of multiple time delays. This paper also focuses on developing Interacting Multiple Model(IMM) Algorithm with multiple model space using Kalman Filter(KF) as state estimator tool. The multiple time delays in power system is considered as multiple model space The result shows that KF provides better estimate of correct model for a particular inputset. The qualitative properties of Riccati difference equation(RDE) in terms of state error covariance of IMMKF are also analyzed and presented.


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