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Design and Simulation of Fuzzy System Using Operational Transconductance Amplifier

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Computational Intelligence in Data Mining - Volume 1

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 31))

Abstract

In this paper a well defined method for the design of fuzzy system using operational transconductance amplifier was discussed. This paper also presents the various types of operational transconductance amplifier: simple OTA, fully differential OTA and Balanced OTA. Proposed model of fully differential OTA and balance OTA is illustrated, out of which balance OTA is the best. Fuzzy system includes fuzzification of the input variables, application of the fuzzy operator (AND or OR) in the antecedent, implication from the antecedent to the consequent, aggregation of the consequents across the rules, and defuzzfication. The fuzzy system (including all blocks) for estimating risk involved in an engineering project has been designed, exhibits a gain of 36.24 dB, input resistance with 44.13 kΩ, output resistance with 2.163 kΩ, CMRR with 47.68 dB, slew rate with 0.6 V/µs and power dissipation with 197 W.

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Authors and Affiliations

  1. Jaypee University of Information Technology, Waknaghat, Solan, Himachal Pradesh, India

    Shruti Jain

Authors
  1. Shruti Jain
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Correspondence to Shruti Jain .

Editor information

Editors and Affiliations

  1. University of Canberra, Canberra, Australia and University of South Australia, Adelaide, South Australia, Australia

    Lakhmi C. Jain

  2. Department of Computer Science and Engineering, Veer Surendra Sai University of Technology, Sambalpur, Odisha, India

    Himansu Sekhar Behera

  3. Computer Science & Engineering, Kalyani University, Nadia, West Bengal, India

    Jyotsna Kumar Mandal

  4. Dept. of Computer Science and Engineering, National Institute of Technology Rourkela, Rourkela, India

    Durga Prasad Mohapatra

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Jain, S. (2015). Design and Simulation of Fuzzy System Using Operational Transconductance Amplifier. In: Jain, L., Behera, H., Mandal, J., Mohapatra, D. (eds) Computational Intelligence in Data Mining - Volume 1. Smart Innovation, Systems and Technologies, vol 31. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2205-7_25

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  • DOI: https://doi.org/10.1007/978-81-322-2205-7_25

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2204-0

  • Online ISBN: 978-81-322-2205-7

  • eBook Packages: EngineeringEngineering (R0)

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