scholarly journals A variational Bayesian robust linear dynamic system approach for dynamic process modelling and fault detection

2015 ◽  
Vol 48 (21) ◽  
pp. 535-540
Author(s):  
Jinlin Zhu Zhiqiang Ge ◽  
Zhihuan Song
Keyword(s):  
Fault Detection ◽  
Dynamic System ◽  
Dynamic Process ◽  
System Approach ◽  
Process Modelling ◽  
Linear Dynamic System ◽  
Variational Bayesian ◽  
Linear Dynamic

A linear dynamic system approach for cattle herd optimal shaping

1997 ◽  
Vol 28 (9) ◽  
pp. 913-918 ◽  
Author(s):  
RICHARDO H. G TAKAHASHI ◽  
CLAUDIA P. CALDEIRA ◽  
PEDRO L. D. PERES
Keyword(s):  
Dynamic System ◽  
System Approach ◽  
Cattle Herd ◽  
Linear Dynamic System ◽  
Linear Dynamic

Automated System Design for Classification of Chronic Lung Viruses using Non-Linear Dynamic System Features and K-Nearest Neighbour

2021 ◽  
Author(s):  
Misha Urooj Khan ◽  
Ayesha Farman ◽  
Asad Ur Rehman ◽  
Nida Israr ◽  
Muhammad Zulqarnain Haider Ali ◽  
...  
Keyword(s):  
Dynamic System ◽  
System Design ◽  
Linear Dynamic System ◽  
Automated System ◽  
Nearest Neighbour ◽  
Linear Dynamic ◽  
Non Linear

Parameter Design in Optimal Control Problems for Linear Dynamic Systems Using a Canonical Form

2013 ◽  
Vol 136 (1) ◽  
Author(s):  
Ui-Jin Jung ◽  
Gyung-Jin Park ◽  
Sunil K. Agrawal
Keyword(s):  
Optimal Control ◽  
Dynamic System ◽  
Dynamic Systems ◽  
Control Method ◽  
Linear Dynamic System ◽  
Parameter Design ◽  
Control Problems ◽  
State Transformation ◽  
Specific System ◽  
Linear Dynamic

Control problems in dynamic systems require an optimal selection of input trajectories and system parameters. In this paper, a novel procedure for optimization of a linear dynamic system is proposed that simultaneously solves the parameter design problem and the optimal control problem using a specific system state transformation. Also, the proposed procedure includes structural design constraints within the control system. A direct optimal control method is also examined to compare it with the proposed method. The limitations and advantages of both methods are discussed in terms of the number of states and inputs. Consequently, linear dynamic system examples are optimized under various constraints and the merits of the proposed method are examined.

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