A discrete state-space model for linear image processing

1975 ◽  
Vol 20 (1) ◽  
pp. 1-10 ◽  
Author(s):  
R. Roesser
2009 ◽  
Vol 58 (6) ◽  
pp. 400-405 ◽  
Author(s):  
Robert J. Elliott ◽  
Jia Deng

Author(s):  
Tadeusz Kaczorek ◽  
Piotr Ostalczyk

AbstractIn this survey we consider two fractional-order discrete state-space models of linear systems. In both cases the crucial elements are the fundamental matrices. The difference between them is analyzed. A fundamental condition for the first state-space model is given. The investigations are illustrated by the numerical examples.


Author(s):  
T. N. Shiau ◽  
M. S. Tsai ◽  
C. H. Cheng

Large vibration of a rotor-bearing system excited by unbalance of rotor shaft or external forces can deteriorate the performance and shorten the lifetime of the system. The hydrodynamic bearing can provide desirable damping for a rotor-bearing system. In order to fully utilize the function of the hydrodynamic bearing for vibration reduction, a state-space technique is developed to identify the parameters (stiffness and damping) of the linearized hydrodynamic bearing. The eigensystem realization algorithm (ERA) is adopted to find the discrete state space model of system. It is shown that the ERA approach can be a very effective way for identification of the rotor-bearing system. The discrete state space model is further transformed to the continuous model that can be utilized to obtain the coefficients for the hydrodynamic bearing system. By comparing the output signal of the identified system and the nonlinear rotor-bearing dynamic model, the identification accuracy is verified. More simulation results on different values of eccentricity are also plotted to show the characteristic of a hydrodynamic bearing.


2014 ◽  
Vol 51 (01) ◽  
pp. 118-135
Author(s):  
Phil Howlett ◽  
Charles Pearce ◽  
Julia Piantadosi

We propose a discrete state-space model for storage of urban stormwater in two connected dams using an optimal pump-to-fill policy to transfer water from the capture dam to the holding dam. We assume stochastic supply to the capture dam and independent stochastic demand from the holding dam. We find new analytic formulae to calculate steady-state probabilities for the contents of each dam and thereby enable operators to better understand system behaviour. We illustrate our methods by considering some particular examples and discuss extension of our analysis to a series of three connected dams.


2014 ◽  
Vol 51 (1) ◽  
pp. 118-135
Author(s):  
Phil Howlett ◽  
Charles Pearce ◽  
Julia Piantadosi

We propose a discrete state-space model for storage of urban stormwater in two connected dams using an optimal pump-to-fill policy to transfer water from the capture dam to the holding dam. We assume stochastic supply to the capture dam and independent stochastic demand from the holding dam. We find new analytic formulae to calculate steady-state probabilities for the contents of each dam and thereby enable operators to better understand system behaviour. We illustrate our methods by considering some particular examples and discuss extension of our analysis to a series of three connected dams.


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