Abstract
Permanent Magnet Synchronous Motors (PMSM) are immensely popular because they can meet the huge capacity needs of industrial applications. Speed regulation of PMSM Drives with conventional Proportional-Integral (PI) regulator reduces the speed control precision because of the disturbances in Motor and load characteristics, leading to poor performance of whole system. The values so obtained may not give satisfactory results in a wide range of speed. In this research, we considered the Mathematical model of speed controller for controlling the speed, which can be formulated as an optimization problem subject to various constraints imposed due to motor and other limitation factors. For solving this problem we used a modified version of Artificial Bee Colony (ABC) algorithm known as Cauchy Mutation ABC (C-ABC).We first illustrate the proposed method using various standard benchmark functions and then it is used for tuning PI controller for speed regulation in PMSM drive. Empirical results obtained are compared with the basic version of ABC, which clearly indicates the superior performance of the C-ABC algorithm.
Keywords
- Permanent Magnet Synchronous Motor
- Controller Tuning
- Bacterial Forage Optimization
- Cauchy Mutate
- Failure Count
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© 2011 Springer-Verlag Berlin Heidelberg
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Rajasekhar, A., Abraham, A., Jatoth, R.K. (2011). Controller Tuning Using a Cauchy Mutated Artificial Bee Colony Algorithm. In: Corchado, E., Snášel, V., Sedano, J., Hassanien, A.E., Calvo, J.L., Ślȩzak, D. (eds) Soft Computing Models in Industrial and Environmental Applications, 6th International Conference SOCO 2011. Advances in Intelligent and Soft Computing, vol 87. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19644-7_2
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DOI: https://doi.org/10.1007/978-3-642-19644-7_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-19643-0
Online ISBN: 978-3-642-19644-7
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