An adaptive liquid level controller using multi sensor data fusion

Research output: Contribution to journalArticle

Abstract

This paper describes a design of adaptive liquid level control system using the concept of Multi Sensor Data Fusion (MSDF). Purpose of the work is to design a controller for accurately controlling the level of liquid in a process tank with liquid temperature changes. The proposed objective is obtained by i) implementing a MSDF framework using Pau's framework for measuring liquid level and temperature, ii) analyzing the behavior of actuator output for variation in liquid temperature, and iii) designing a suitable adaptive controller which will produce desired control action for controlling liquid level accurately using neural network algorithms. Outputs from sensors are fused to obtain the fluid level output and also relation of level transmitter output for change in temperature. This information is used by controller to train the neural network so as to tune the controller parameters (proportional gain, integral constant, and differential constant), to drive the actuator. Results obtained show that the system is able to control liquid level within range of 1.915% of set point even with variations in liquid temperature.

Original languageEnglish
Pages (from-to)2465-2473
Number of pages9
JournalTelkomnika (Telecommunication Computing Electronics and Control)
Volume16
Issue number5
DOIs
Publication statusPublished - 01-10-2018

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Sensor data fusion
Controllers
Liquids
Actuators
Temperature
Neural networks
Level control
Transmitters
Control systems
Fluids
Sensors

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Cite this

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title = "An adaptive liquid level controller using multi sensor data fusion",
abstract = "This paper describes a design of adaptive liquid level control system using the concept of Multi Sensor Data Fusion (MSDF). Purpose of the work is to design a controller for accurately controlling the level of liquid in a process tank with liquid temperature changes. The proposed objective is obtained by i) implementing a MSDF framework using Pau's framework for measuring liquid level and temperature, ii) analyzing the behavior of actuator output for variation in liquid temperature, and iii) designing a suitable adaptive controller which will produce desired control action for controlling liquid level accurately using neural network algorithms. Outputs from sensors are fused to obtain the fluid level output and also relation of level transmitter output for change in temperature. This information is used by controller to train the neural network so as to tune the controller parameters (proportional gain, integral constant, and differential constant), to drive the actuator. Results obtained show that the system is able to control liquid level within range of 1.915{\%} of set point even with variations in liquid temperature.",
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