Adaptive Neural Fuzzy Inference System Optimization in Converter
A new technique of AFIS speed control of DC drives with Asymmetrical Half-Bridge converter is proposed. The PI controller is the most common feedback controller used in the process industries. PI is easily understood algorithm, which give good control action of varied dynamic characteristics.
However, PI controller have drawback of not giving the optimum response for non-linear systems. By the introduction of novel intelligent techniques, the PI controller and FLC are optimized by Adaptive Neural Fuzzy Inference Systems. In this paper the ANFIS optimization method is applied for
speed control of DC to DC converter fed drive. The main motive of this work is to attain minimum transient and switching losses to decrease the energy loss by which the efficiency gets increased.
Keywords: Adaptive Neural Fuzzy Inference Systems (ANFIS); Direct Current (DC); Fuzzy Logic Controller (FLC); Proportional Integral (PI); Ripple
Document Type: Research Article
Affiliations: 1: Department of Electrical and Electronics Engineering, Research Scholar Sathyabama University, Chennai 600119; AP in Jeppiaar SRR Engineering College, Chennai 603103, Tamilnadu, India 2: Department of Electrical and Electronics Engineering, S. A. Engineering College, Chennai 600077, Tamilnadu, India
Publication date: 01 January 2017
- Journal of Computational and Theoretical Nanoscience is an international peer-reviewed journal with a wide-ranging coverage, consolidates research activities in all aspects of computational and theoretical nanoscience into a single reference source. This journal offers scientists and engineers peer-reviewed research papers in all aspects of computational and theoretical nanoscience and nanotechnology in chemistry, physics, materials science, engineering and biology to publish original full papers and timely state-of-the-art reviews and short communications encompassing the fundamental and applied research.
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