Development of a virtual linearizer for correcting transducer static nonlinearity

This paper reports the development of an artificial neural network based virtual linearizer for correcting nonlinearity associated with transducers connected to the data-acquisition system of a computer-based measurement system. In analog processing techniques, nonlinearity is considered to be a ver...

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Bibliographic Details
Published in:ISA transactions 2006-07, Vol.45 (3), p.319-328
Main Authors: Singh, Amar Partap, Kamal, Tara Singh, Kumar, Shakti
Format: Article
Language:English
Subjects:
Algorithms
Applied sciences
Artificial neural network
Computer science
control theory
systems
Computer Simulation
Control theory. Systems
Exact sciences and technology
General equipment and techniques
Instruments, apparatus, components and techniques common to several branches of physics and astronomy
Inverse model
Linear Models
Linearizer
Nonlinear Dynamics
Nonlinearity
Physics
Servo and control equipment
robots
Software
Transducer
Transducers
User-Computer Interface
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Summary:This paper reports the development of an artificial neural network based virtual linearizer for correcting nonlinearity associated with transducers connected to the data-acquisition system of a computer-based measurement system. In analog processing techniques, nonlinearity is considered to be a very serious problem that at one time was solved frequently by the piecewise linear segment approach modeled by linear electronic circuits. Since the cost of microcomputers has been reduced drastically, they are currently used in most applications of measurement, including data-acquisition subsystems. Therefore, the hardware-based analog techniques of linearization are often replaced by the software-based numerical ones. In this context, it has been found that a multilayer feed-forward back-propagation network trained with the Levenberg-Marquardt learning rule provides an optimal solution to implement an efficient soft compensator to correct transducer static-nonlinearity.
ISSN:0019-0578
1879-2022
DOI:10.1016/S0019-0578(07)60215-8