Hardware/firmware implementation of a soft sensor using an improved version of a fuzzy identification algorithm.
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.
Garcia
Claudio
C
Automation 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
de Carvalho Berni
Cássio
C
de Oliveira
Carlos Eduardo Neri
CE