Title :
Neuro-fuzzy sensor´s linearization based FPGA
Author :
Bouhedda, Mounir
Author_Institution :
Lab. of Adv. Electron. Syst. (LSEA), Univ. of Medea, Medea, Algeria
Abstract :
Nonlinear sensors and digital solutions are used in many embedded system designs. As the input/output characteristic of most sensors is nonlinear in nature, obtaining data from a nonlinear sensor by using an optimized device has always been a design challenge. This paper aims to propose a new Adapive Neuro-Fuzzy Inference System (ANFIS) digital architecture based Field Programmable Gate Array (FPGA) to linearize the sensor´s characteristic. The ANFIS linearizer in synthesized and optimized in view to digital linearization. The performance of the developed architecture is examined with comparison to ANFIS software model and with two other designed architectures based FPGA using classical techniques. The results show the successful of the proposed architecture by demonstrating the capability of the operation to linearize a temperature sensor characteristic.
Keywords :
computerised instrumentation; field programmable gate arrays; fuzzy neural nets; inference mechanisms; intelligent sensors; linearisation techniques; software architecture; ANFIS digital architecture; ANFIS linearizer; ANFIS software model; FPGA; adapive neuro-fuzzy inference system digital architecture; digital solutions; field programmable gate array; neuro-fuzzy sensor linearization; nonlinear sensors; optimized device; temperature sensor; Computer architecture; Field programmable gate arrays; Hardware; Integrated circuit modeling; Sensor phenomena and characterization; Temperature sensors; FPGA; Linearization; Neuro-Fuzzy; Sensor;
Conference_Titel :
Intelligent Data Acquisition and Advanced Computing Systems (IDAACS), 2013 IEEE 7th International Conference on
Conference_Location :
Berlin
Print_ISBN :
978-1-4799-1426-5
DOI :
10.1109/IDAACS.2013.6662698