Abstract
Intelligent control techniques that emulate characteristics of biological systems offer opportunities for creating control products with new capabilities. In today’s competitive economic environment, these control techniques can provide products with the all-important competitive edge that companies seek. However, while numerous applications of intelligent control (IC) have been described in the literature, few advance past the simulation stage to become laboratory prototypes, and only a handful make their way into products. The ability of research to impact products hinges not so much on finding the best solution to a problem, but on finding the right problem and then solving it in a marketable way [1].
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
Chiu S (1997) Developing commercial applications of intelligent control. IEEE Control Syst Mag 17(2):94–100
Encyclopedia Britannica (2009) Intelligence. http://www.britannica.com/EBchecked/topic/289766/human-intelligence. Accessed on 22 March 2009
Jang J-SR (1993) ANFIS: Adaptive network-based fuzzy inference systems. IEEE Trans Syst Man Cybernet 23:665–685
Karr CL (2003) Control of a phosphate processing plant via a synergistic architecture. Eng Appl Artif Intell 6(1):21–30
Van Rooij AJF (1996) Neural network training using genetic algorithms. World Scientific, River Edge, NJ
Sanchez E, Shibata T, Zadeh LA (1997) Genetic algorithms and fuzzy logic systems. Advances in fuzzy systems: application and theory, Vol. 7. World Scientific, River Edge, NJ
Kosko B (1991) Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence. Prentice Hall, New York
Goonatilake S, Khebbal S (eds) (1996) Intelligent hybrid systems. Wiley, New York
Medsker LR (1995) Hybrid intelligent systems. Kluwer, Dordrecht
Schwartz DG, Klir GJ (1992) Fuzzy logic flowers in Japan. IEEE Spectrum 29(7):32–35
Zilouchian A, Jamshidi M (2001) Intelligent control systems using soft computing methodologies. CRC, Boca Raton, FL
Warwick K (1998) Recent developments in intelligent control. IEE Colloquium on Updates on Developments in Intelligent Control, Oct 1998, pp 1/1–1/4
Josifovska S (2003) The father of LabVIEW. IEE Rev 49(9):30–33
Kehtarnavaz N, Gope C (2006) DSP system design using LabVIEW and Simulink: a comparative evaluation. Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Toulouse, France, 14–19 May 2006, Vol. 2, pp II–II
ITESM Mexico (2007) Intelligent Control Toolkit for LabVIEW. US Patent Application 61/197,484
National Instruments (2009) http://www.ni.com. Accessed on 22 March 2009
Rights and permissions
Copyright information
© 2010 Springer-Verlag London Limited
About this chapter
Cite this chapter
(2010). Intelligent Control for LabVIEW. In: Intelligent Control Systems with LabVIEW™. Springer, London. https://doi.org/10.1007/978-1-84882-684-7_1
Download citation
DOI: https://doi.org/10.1007/978-1-84882-684-7_1
Publisher Name: Springer, London
Print ISBN: 978-1-84882-683-0
Online ISBN: 978-1-84882-684-7
eBook Packages: EngineeringEngineering (R0)