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IJMLC 2019 Vol.9(4): 413-418 ISSN: 2010-3700
DOI: 10.18178/ijmlc.2019.9.4.819

High Performance Sine Wave Inverters Using Simulated Annealing Algorithm Tuned Non-Real-Valued Sliding Surface

En-Chih Chang, Chun-An Cheng, and Rong-Ching Wu

Abstract—In this paper, a simulated annealing algorithm tuned non-real-valued sliding surface is developed to enhance the transience and steady-state response of sine wave inverters. Even if the customary sliding surface (CSS) has the insensitivity to system uncertainties, the model of a reduced order exists in sliding action, thus yielding deficient system dynamics. By employing the non-real-valued sliding surface (NRVSS), the entire system dynamics can be established. Unfortunately, the occurrence of the chatter phenomenon is frequent and the harmonic distortion of sine wave inverter output is also high. To effectively reject the effect of the chatter, the NRVSS control gains can be optimally tuned via the simulated annealing algorithm (SAA). The proposed methodology has been implemented for the actual sine wave inverter controlled by a digital signal processor (DSP). Experimental results of the closed-loop system represent that the proposed methodology can provide fast transient response, low total harmonic distortion (THD) and the attenuation of steady-state error and chatter.

Index Terms—Non-real-valued sliding surface (NRVSS), chatter phenomenon, sine wave inverter, simulated annealing algorithm (SAA), total harmonic distortion (THD).

The authors are with the Department of Electrical Engineering, I-Shou University, Kaohsiung City 84001, Taiwan (Corresponding Author e-mail: enchihchang@isu.edu.tw, cacheng@isu.edu.tw, rcwu@isu.edu.tw).


Cite: En-Chih Chang, Chun-An Cheng, and Rong-Ching Wu, "High Performance Sine Wave Inverters Using Simulated Annealing Algorithm Tuned Non-Real-Valued Sliding Surface," International Journal of Machine Learning and Computing vol. 9, no. 4, pp. 413-418, 2019.

Copyright © 2019 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

General Information

  • E-ISSN: 2972-368X
  • Abbreviated Title: Int. J. Mach. Learn.
  • Frequency: Quaterly
  • DOI: 10.18178/IJML
  • Editor-in-Chief: Dr. Lin Huang
  • Executive Editor:  Ms. Cherry L. Chen
  • Abstracing/Indexing: Inspec (IET), Google Scholar, Crossref, ProQuest, Electronic Journals LibraryCNKI.
  • E-mail: ijml@ejournal.net

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