Abstract
In this paper a Multi-Objective Particle Swarm Optimization (MOPSO) is utilized to design sets of linguistic Fuzzy Logic Controller (FLC) type Mamdani to govern the speed of Induction Motor (IM). The first objective function is the error between the actual speed and desired speed, and the second function is the energy dissipated during (10 Sec). PSO are implemented in M-file/MATLAB, but when the algorithm reaches the step of assessing the “fitness functions”, this program linked with SIMULINK-MATLAB to evaluate these values. This simulation includes the complete mathematical model of IM and the inverter. The simulation results show the proposed controller offers an optimized speed behavior as possible with a low-slung of energy along the points of Pareto front.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Wlas, M., Abu-Rub, H., Holtz, J.: Speed Sensorless Nonlinear Control Of Induction Motor in The Field Weakening Region. In: IEEE 13th International Power Electronics and Motion Control Conference, pp. 1084–1089 (2008)
Dubey, M.: Design of Genetic Algorithm Based Fuzzy Logic Power System Stabilizers in Multimachine Power System. In: POWERCON 2008 & Power India Conference, October 12-15, IEEE, New Delhi (2008)
Rapaic, M.R., Kanovic, Z., Jelicic, Z.D.: A Theoretical and Empirical Analysis of Convergence Related Particle Swarm Optimization. Wseas Transactions on Systems and Control 11(4) (November 2009)
Bachache, N.K., Wen, J.: Particle swarm optimize fuzzy logic memberships of AC-drive. In: Tan, Y., Shi, Y., Ji, Z. (eds.) ICSI 2012, Part I. LNCS, vol. 7331, pp. 460–469. Springer, Heidelberg (2012)
Kung, Y.-S., Wang, M.-S., Huang, C.-C.: Digital Hardware Implementation of Adaptive Fuzzy Controller for AC Motor Drive. In: The 33rd Annual Conference of the IEEE Industrial Electronics Society (IECON), Taipei, Taiwan (2007)
Keskar, A.G., Asanare, K.L.: Floating Membership Fuzzy Logic Controller For Adaptive Control Of AC Drive. In: IEEE Catalog Number: 97TH8280ISIE 1997 - Guhariies, Portugal (1997)
Martinez, F., Gastiblanco, M.: Increase the Boost Converter Performance Using Genetic Algorithms. Online Journal on Electronics and Electrical Engineering 2(1) (2008)
Allaoua, B., Laaoufi, A.: Intelligent Controller Design for DC Motor Speed Control Based on Fuzzy Logic-Genetic Algorithms Optimization. Leonardo Journal of Sience (13), 90–102 (2008)
Benachaiba, C., Abdel Khalek, O., Dib, S.: Optimization of Parameters of the Unified Power Quality Conditioner Using Genetic Algorithm Method. Information Technology and Control 36(2) (2007) ISSN 1392
Davis, L.: A Handbook of Genetic Algorithm. Van Nostrand Reinhold, New York (1990)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Bachache, N.K., Wen, J. (2013). Multi Objective Swarm Optimization Design Fuzzy Controller to Adjust Speed of AC Motor Drive. In: Tan, Y., Shi, Y., Mo, H. (eds) Advances in Swarm Intelligence. ICSI 2013. Lecture Notes in Computer Science, vol 7928. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38703-6_61
Download citation
DOI: https://doi.org/10.1007/978-3-642-38703-6_61
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-38702-9
Online ISBN: 978-3-642-38703-6
eBook Packages: Computer ScienceComputer Science (R0)