Simple design procedure for single-sideband crystal filters

1977 ◽  
Vol 13 (23) ◽  
pp. 687
Author(s):  
J.L. Haine
Author(s):  
G. Fusco ◽  
M. Russo

This paper proposes a simple design procedure to solve the problem of controlling generator transient stability following large disturbances in power systems. A state-feedback excitation controller and power system stabilizer are designed to guarantee robustness against uncertainty in the system parameters. These controllers ensure satisfactory swing damping and quick decay of the voltage regulation error over a wide range of operating conditions. The controller performance is evaluated in a case study in which a three-phase short-circuit fault near the generator terminals in a four-bus power system is simulated.


2000 ◽  
Vol 126 (11) ◽  
pp. 1372-1374
Author(s):  
John H. Scarino ◽  
Daniël Vandepitte ◽  
A. A. El Damatty ◽  
R. M. Korol ◽  
M. El Attar

Geophysics ◽  
2007 ◽  
Vol 72 (2) ◽  
pp. S105-S112 ◽  
Author(s):  
Rune Mittet

I compensate for the effects of absorption and dispersion in deriving the space-frequency domain depth extrapolation operators by starting from the ones without such compensation. The procedure is simple and requires only trivial cosine transforms applied to the original noncompensating operators. I show that compensating operators enhance resolution as a function of depth when applied in prestack depth migration.


1994 ◽  
Vol 16 (5) ◽  
pp. 377-385 ◽  
Author(s):  
Murray J. Clarke ◽  
Gregory J. Hancock

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Biswa Binayak Mangaraj ◽  
Manas Ranjan Jena ◽  
Saumendra Kumar Mohanty

A simple design procedure to realize an optimum antenna using bacteria foraging algorithm (BFA) is proposed in this paper. The first antenna considered is imaginary. This antenna is optimized using the BFA along with a suitable fitness function formulated by considering some performance parameters and their best values. To justify the optimum design approach, one 12-element Yagi-Uda antenna is considered for an experiment. The optimized result of this antenna obtained using the optimization algorithm is compared with nonoptimized (conventional) result of the same antenna to appreciate the importance of optimization.


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