Hardware/firmware implementation of a soft sensor using an improved version of a fuzzy identification algorithm
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Published on: March 13, 2017
Claudio Garcia1, Cássio de Carvalho Berni, Carlos Eduardo Neri de Oliveira
1Automation and Control Laboratory, Department of Telecommunications and Control Engineering, Polytechnic School of the University of São Paulo, Av. Prof. Luciano Gualberto, trav. 3-n. 380-CEP: 05508-900-São Paulo, SP, Brazil. claudio.garcia@poli.usp.br
Abstract:
This paper presents the design and implementation of an embedded soft sensor, i.e., a generic and autonomous hardware module, which can be applied to many complex plants, wherein a certain variable cannot be directly measured. It is implemented based on a fuzzy identification algorithm called "Limited Rules", employed to model continuous nonlinear processes. The fuzzy model has a Takagi-Sugeno-Kang structure and the premise parameters are defined based on the Fuzzy C-Means (FCM) clustering algorithm. The firmware contains the soft sensor and it runs online, estimating the target variable from other available variables. Tests have been performed using a simulated pH neutralization plant. The results of the embedded soft sensor have been considered satisfactory. A complete embedded inferential control system is also presented, including a soft sensor and a PID controller.
