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An enhanced fuzzy controller based on improved genetic algorithm for speed control of DC motors
Because of being imprecision and existence of uncertainty in input variables to fuzzy systems, and also their easy implementation, fuzzy controllers are introduced as one of useful optimization tools in industry especially in DC motors. Given to the growth of controller systems usages in industry, u...
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Published in: | Analog integrated circuits and signal processing 2020-11, Vol.105 (2), p.141-155 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Because of being imprecision and existence of uncertainty in input variables to fuzzy systems, and also their easy implementation, fuzzy controllers are introduced as one of useful optimization tools in industry especially in DC motors. Given to the growth of controller systems usages in industry, use of optimization methods has been noticed in the recent years; so that improve precision and performance of these systems. In addition to making improvement in their performance, real time implementation, less energy spending in comparison with other tools, having high speed in mathematical computation and decreasing hardware resources consumption are some serious challenges in this terrain. To optimize fuzzy controllers’ performance, various methods have been proposed by the researchers. This paper firstly focuses on applying improved Genetic Algorithm in regulating optimum parameters of fuzzy controller to rise convergence speed and accuracy. Secondly, a pipeline technique with specific strategies of diminishing required bit width for fuzzy controllers is provided to achieve maximum efficiency in fuzzy controller implementation. In general, it can be seen that optimized fuzzy controller in this paper has precise performance, high convergence speed and such advantages in efficient hardware implementation in comparison with other fuzzy controllers. |
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ISSN: | 0925-1030 1573-1979 |
DOI: | 10.1007/s10470-020-01599-9 |