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Power Quality Improvement using Improved Approximated Fuzzy Logic Controller for Shunt Active Power Filter

Power Quality Improvement using Improved Approximated Fuzzy Logic Controller for Shunt Active Power Filter

Asheesh K. Singh, Rambir Singh
Copyright: © 2014 |Pages: 23
ISBN13: 9781466660984|ISBN10: 1466660988|EISBN13: 9781466660991
DOI: 10.4018/978-1-4666-6098-4.ch011
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MLA

Singh, Asheesh K., and Rambir Singh. "Power Quality Improvement using Improved Approximated Fuzzy Logic Controller for Shunt Active Power Filter." Systems and Software Development, Modeling, and Analysis: New Perspectives and Methodologies, edited by Mehdi Khosrow-Pour, D.B.A., IGI Global, 2014, pp. 310-332. https://doi.org/10.4018/978-1-4666-6098-4.ch011

APA

Singh, A. K. & Singh, R. (2014). Power Quality Improvement using Improved Approximated Fuzzy Logic Controller for Shunt Active Power Filter. In M. Khosrow-Pour, D.B.A. (Ed.), Systems and Software Development, Modeling, and Analysis: New Perspectives and Methodologies (pp. 310-332). IGI Global. https://doi.org/10.4018/978-1-4666-6098-4.ch011

Chicago

Singh, Asheesh K., and Rambir Singh. "Power Quality Improvement using Improved Approximated Fuzzy Logic Controller for Shunt Active Power Filter." In Systems and Software Development, Modeling, and Analysis: New Perspectives and Methodologies, edited by Mehdi Khosrow-Pour, D.B.A., 310-332. Hershey, PA: IGI Global, 2014. https://doi.org/10.4018/978-1-4666-6098-4.ch011

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Abstract

This chapter presents the design approach of an Improved Approximated Simplest Fuzzy Logic Controller (IASFLC). A cascade combination of simplest 4-rule Fuzzy Logic Controller (FLC) and an nth degree polynomial is proposed as an IASFLC to approximate the control characteristics of a 49-rule FLC. The approximation scheme is based on minimizing the sum of square errors between the control outputs of a 49-rule FLC and a simplest 4-rule FLC in the entire range of Universe Of Discourse (UOD). The coefficients of compensating polynomial are evaluated by solving instantaneous square error equations at various test points in the entire UOD. This IASFLC maps the output of a 49-rule FLC with absolute deviation of less than 5%. The proposed IASFLC is used to control the dc link voltage of a three-phase shunt Active Power Filter (APF). A detailed analysis is performed during transient and steady state conditions to check Power Quality (PQ) and dynamic performance indices under randomly varying balanced and unbalanced loading conditions. The performance of proposed IASFLC is compared with a 49-rule FLC and Approximated Simplest Fuzzy Logic Controller (ASFLC) based on minimization of the deviation at central values of Membership Functions (MFs). It is found comparatively better for harmonic and reactive compensation with a comparable dynamic response. The memory requirement and computational time of proposed IASFLC are even lesser than the ASFLC.

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