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Author: search.filters.author.Bhanot, SurekhaSubject: search.filters.subject.Fuzzy logic

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    Differential evolution based optimal fuzzy logic control of pH neutralization process
    (IEEE, 2014) Bhanot, Surekha; Mohanta, Hare Krishna
    Differential evolution (DE) is a member of evolutionary algorithm family which has gained popularity due to its conceptual simplicity and better convergence. This paper presents fuzzy logic based pH control scheme for neutralization process in which DE is used to optimize the input and output membership functions of fuzzy inference system (FIS). The fitness function for optimization is integral of squared errors (ISE). DE is able to converge and find optimal global solution over narrow as well as wide search spaces. Finally the controller performance has been evaluated for servo and regulatory operations.
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    Fuzzy Query Processing in Distributed databases
    (ICAISC, 2016) Bhanot, Surekha
    The problem of evolving databases to make them more intuitive, user-friendly and to be able to answer vague human queries with separate needs for each user has become a popular research topic. The solution to this problem in part has been proposed via databases that aim at inserting fuzzy data into databases hence handling vague human like queries. It has been suggested in many research papers that fuzziness may be applied to databases. However, this approach is infeasible and inefficient for real time processing. In the past 30 years of research, fuzzy databases are still not popular in industry because of unwillingness of companies to replace crisp data with fuzzy data in their databases due to excessive precomputation and possible chances of data inconsistency. Having fuzzy databases also places severe constraints on the database as it will become very difficult to run crisp queries on fuzzy databases. This problem becomes even more complex with the advent of “Big Data”. This paper proposes a three pronged fuzzy logic based technique as a layer of computation above traditional query processing to solve such queries in real time. This fuzzy logic based approach to querying in distributed databases can be used to solve ambiguous queries, incorporating the preferences of each user in the current scenario of excessive data. The results obtained using the fuzzy logic approach are compared with those obtained using traditional approach in terms of accuracy, time taken for each approach and closeness of the results to users requirements.
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    Neural Control of Neutralization Process using Fuzzy Inference System based Lookup Table
    (IJCA, 2021-10-20) Mohanta, Hare Krishna; Bhanot, Surekha
    Over a number of years, pH control of neutralization process is recognized as a benchmark for modeling and control of nonlinear processes. This paper first describes dynamic modeling of pH neutralization process. Thereafter fuzzy logic based pH control scheme for neutralization process is developed. Further, a two-dimensional (2-D) lookup table is generated based on defuzzification mechanism of fuzzy inference system (FIS). Finally, using this lookup table, a neural network control for pH neutralization process is developed. Performances of fuzzy logic based control and lookup table based neural network control for servo and regulatory operations are compared based on integral square error (ISE) and integral absolute error (IAE) criterions. Results indicate that lookup table based neural network control performs better than fuzzy logic based control.