Study of PID and FLC based water level control using ultrasonic level detector

2016 ◽  
Author(s):  
Bikas Mondal ◽  
Sourav Rakshit ◽  
Rajan Sarkar ◽  
Nirupama Mandal
Keyword(s):  
Water Level ◽  
Level Control ◽  
Level Detector

Water Level Control of Small-scale Hydroelectric Power Plant

2002 ◽  
Vol 122 (6) ◽  
pp. 989-994
Author(s):  
Shinichiro Endo ◽  
Masami Konishi ◽  
Hirosuke Imabayashi ◽  
Hayami Sugiyama
Keyword(s):  
Power Plant ◽  
Water Level ◽  
Hydroelectric Power Plant ◽  
Small Scale ◽  
Hydroelectric Power ◽  
Level Control

Model Predictive Control for Water Level Control in the Case of Spills

2017 ◽  
Vol 143 (3) ◽  
Author(s):  
Xin Tian ◽  
Boran Ekin Aydin ◽  
Rudy R. Negenborn ◽  
Nick van de Giesen ◽  
José María Maestre
Keyword(s):  
Model Predictive Control ◽  
Water Level ◽  
Predictive Control ◽  
Level Control

scholarly journals STEAM GENERATOR WATER LEVEL CONTROL

1964 ◽  
Author(s):  
A. N. Nahavandi ◽  
A. Batenburg
Keyword(s):  
Water Level ◽  
Steam Generator ◽  
Level Control

scholarly journals A hybrid PSO-PID approach for trajectory tracking application of a liquid level control process

2015 ◽  
Vol 5 (2) ◽  
pp. 63-73 ◽  
Author(s):  
Turker Tekin Erguzel
Keyword(s):  
Water Level ◽  
Pid Controller ◽  
Nuclear Power ◽  
Power Plants ◽  
Control Process ◽  
Nonlinear Process ◽  
Reference Trajectory ◽  
Proportional Integral Derivative ◽  
Level Control ◽  
Steam Generators

Water level control is a crucial step for steam generators (SG) which are widely used to control the temperature of nuclear power plants. The control process is therefore a challenging task to improve the performance of water level control system. The performance assessment is another consideration to underline. In this paper, in order to get better control of water level, the nonlinear process was first expressed in terms of a transfer function (TF), a proportional-integral-derivative (PID) controller was then attached to the model. The parameters of the PID controller was finally optimized using particle swarm optimization (PSO). Simulation results indicate that the proposed approach can make an effective tracking of a given level set or reference trajectory.

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