Abstract
This paper proposes the particle swarm optimization (PSO) of type-2 membership functions for average approximation of an interval type-2 fuzzy logic system (AT2-FIS), the AT2-FIS is synthesized in VHDL code for FPGAs. The PSO method considers three objective functions, overshoot, undershoot and steady state error because the real application is to control the speed of a DC motor. Several experiments were performed to optimize the AT2-FIS in FPGA. Experiments were conducted by changing the number of bits for encoding the AT2-FLC in VHDL.
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
Clerk, M.: Particle Swarm Optimization. ISTE Ltd. (2006)
Klir, G.J., Mark, J.W.: Uncertainty Based Information: Elements of Generalized Information Theory. Physica-Verlag (1999)
Man, K.F., Tang, K.S., Kwong, S.: Genetic algorithms. Springer (2000)
Maldonado, Y., Castillo, O., Melin, P.: Design of a Type-2 Fuzzy Controller and its Comparison with Type-1 Fuzzy and PID Controllers for Velocity Regulation in a DC Motor. In: Proceedings of the World Conference on Soft Computing (WConSC 2011), pp. 1–6 (2011)
Mendel, J.M.: Uncertainty Rule Based Fuzzy Logic Systems: Introduction and New Directions. Prentice-Hall, Upper-Saddle River (2001)
Mendel, J.M.: Type-2 Fuzzy Sets and Systems: an Overview. IEEE Computational Intelligence Magazine 2, 20–29 (2007)
Montiel, O., Sepúlveda, R., Maldonado, Y., Castillo, O.: Design and Simulation of the Type-2 Fuzzification Stage: Using Active Membership Functions. In: Castillo, O., Pedrycz, W., Kacprzyk, J. (eds.) Evolutionary Design of Intelligent Systems in Modeling, Simulation and Control. SCI, vol. 257, pp. 273–293. Springer, Heidelberg (2009)
Sepulveda, R., Castillo, O., Melin, P., Montiel, O.: An Efficient Computational Method to Implement Type-2 Fuzzy Logic in Control Applications Analysis and Design of Intelligent Systems Using Soft Computing Techniques. In: Advances in Soft Computing, vol. 41, pp. 45–52. Springer (2007)
Sepulveda, R., Montiel, O., Olivas, J.A., Castillo, O.: Methodology to Test and Validate a VHDL Inference Engine of a Type-2 FIS, Through the Xilinx System Generator. In: Evolutionary Design of Intelligent Systems in Modeling, Simulation and Control, pp. 295–308. Springer (2009)
Zadeh, L.A.: Fuzzy Sets. Information and Control 8, 338–353 (1965)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Maldonado, Y., Castillo, O., Melin, P. (2013). Particle Swarm Optimization for Average Approximation of Interval Type-2 Fuzzy Inference Systems Design in FPGAs for Real Applications. In: Castillo, O., Melin, P., Kacprzyk, J. (eds) Recent Advances on Hybrid Intelligent Systems. Studies in Computational Intelligence, vol 451. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33021-6_3
Download citation
DOI: https://doi.org/10.1007/978-3-642-33021-6_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33020-9
Online ISBN: 978-3-642-33021-6
eBook Packages: EngineeringEngineering (R0)