Abstract
This paper focuses on the Gravitational Search Algorithm (GSA) which depends on the law of gravity and law of motion. GSA lacks the exploitation property. To improve the exploitation skill, efficiency, and accuracy of GSA, a modified GSA (MGSA) is proposed. The proposed algorithm keeps up a suitable stability between the exploitation and exploration skills of GSA by using an intelligence factor (IF). The MGSA is applied to speed control problem of an induction motor system. Simulations results showed that the modified GSA performs better than GSA and Adaptive Tabu Search (ATS) in terms of computational time and closed-loop response.
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References
Katsuhiko Ogata. Modern control engineering. Prentice Hall PTR, 2001.
Saha-guHadan-dong. A realization fuzzy pi and fuzzy pd controller using a compensation fuzzy algorithms. 2002.
D Puangdownreong, T Kulworawanichpong, and S Sujitjorn. Input weight-ing optimization for pid controllers based on the adaptive tabu search. Proc. IEEE TENCON 2004, 4:451–454, 2004.
Khaled Halbaoui, DjamelBoukhetala, and FarèsBoudjema. Hybrid adaptive control for speed regulation of an induction motor drive. Archives of Control Sciences, 19(2), 2009.
Jianan Wang, Chunming Li, and Huiling Li. The application of integral sliding mode variable structure in induction motor vector control system. In 2010 2nd International Conference on Mechanical and Electronics Engineering, 2010.
Luis Ibarra, Pedro Ponce, and Arturo Molina. Robust qft-based control of dtc-speed loop of an induction motor under di erent load conditions. IFAC-Papers Online, 48(3):2429–2434, 2015.
EsmatRashedi, Hossein Nezamabadi-Pour, and SaeidSaryazdi. Gsa: a gravitational search algorithm. Information sciences, 179(13):2232–2248, 2009.
Chang KyooYoo, Dong Soon Kim, Ji-Hoon Cho, Sang Wook Choi, and In-Beum Lee. Process system engineering in wastewater treatment process. Korean Journal of Chemical Engineering, 18(4):408–421, 2001.
MA Behrang, E Assareh, M Ghalambaz, MR Assari, and AR Noghrehabadi. Forecasting future oil demand in iran using gsa (gravitational search algo-rithm). Energy, 36(9):5649–5654, 2011.
SerhatDuman, UğurGüven¸c, Yusuf Sönmez, and NuranYorükeren. Optimal power flow using gravitational search algorithm. Energy Conversionand Management, 59:86–95, 2012.
Rabindra Kumar Sahu, Sidhartha Panda, and SarojPadhan. Optimal gravitational search algorithm for automatic generation control of interconnected power systems. Ain Shams Engineering Journal, 5(3):721–733, 2014.
Jen-Hsing Li and Juing-ShianChiou. Gsa-tuning ipd control of a field-sensed magnetic suspension system. Sensors, 15(12):31781–31793, 2015.
Ghang-Ming Liaw and Faa-Jeng Lin. A robust speed controller for induction motor drives. Industrial Electronics, IEEE Transactions on, 41(3):308–315, 1994.
DeachaPuangdownreong and SupapornSuwannarongsri. Application of eitelberg’s method for pi controllers via particle swarm optimization. In Control, Automation, Robotics and Vision, 2008. ICARCV 2008. 10th International Conference on, pages 566–570. IEEE, 2008.
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Rathore, A., Bhandari, M. (2018). Parameter Estimation for PID Controller Using Modified Gravitational Search Algorithm. In: Bhatia, S., Mishra, K., Tiwari, S., Singh, V. (eds) Advances in Computer and Computational Sciences. Advances in Intelligent Systems and Computing, vol 554. Springer, Singapore. https://doi.org/10.1007/978-981-10-3773-3_4
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DOI: https://doi.org/10.1007/978-981-10-3773-3_4
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