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Design of Low-Voltage CMOS Op-Amp Using Evolutionary Optimization Techniques

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Advances in Computer Communication and Computational Sciences

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 759))

Abstract

The comparative optimizing efficiency of particle swarm optimization (PSO) and simplex particle swarm optimization (Simplex-PSO) method is explored in this work. A CMOS operational amplifier (Op-Amp) with low voltage has been optimized using this method. The concept of PSO is based on communal manner of bird flocking. PSO suffers from stagnation problem and premature convergence. Nelder–Mead simplex method (NMSM) is hybridized with PSO to produce simplex-PSO. Simplex-PSO is very fast and efficient optimization technique. Simplex-PSO gives high accuracy in terms of computational complexity. The main idea is to reduce the overall circuit’s area of low-voltage CMOS op-amp. PSO and simplex-PSO based optimized results are verified by SPICE. SPICE-based results demonstrate that the design and essential specifications are approximately reached. Simplex-PSO shows the better optimizing efficiency than PSO for the designed circuit.

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References

  1. Kennedy, Eberhart, R.: Particle swarm optimization. In: Proceedings of IEEE International Conference On Neural Network, vol. 4, pp. 1942–1948 (1995)

    Google Scholar 

  2. Eberhart, R., Shi, Y.: Comparison between genetic algorithm and particle swarm optimization. Evolutionary Programming-VII, pp. 611–616. Springer (1998)

    Google Scholar 

  3. Vural, R.A., Yildirim, T.: Analog circuit sizing via swarm intelligence. AEU Int. J. Electron. Commun. 66(9), 732–740 (2012)

    Article  Google Scholar 

  4. Vural, R.A., Yildirim, T.: Swarm intelligence based sizing methodology for CMOS operational amplifier. In: Proceedings of 12th IEEE Symposium on Computational Intelligence and Informatics, pp. 525–528 (2011)

    Google Scholar 

  5. Ceperic, V., Butkovic, Z., Baric, A.: Design and optimization of self-biased complementary folded cascode. In: Proceedings of IEEE Mediterranean Electrotechnical Conference (MELECON), pp. 145–148 (2006)

    Google Scholar 

  6. Liu, B., Wang, Y., Yu, Z., Liu, L., Li, M., Wang, Z., Lu, J., Fernandez, F.V.: Analog circuit optimization system based on hybrid evolutionary algorithms. Integr. VLSI J. 42, 137–148 (2009)

    Article  Google Scholar 

  7. Hershenson, M., Boyd, S.P., Lee, T.H.: Optimal design of a CMOS op-amp via geometric programming. IEEE Trans. Comput. Aided Des. Integr. Circ. Syst. 20, 1–21 (2001)

    Article  Google Scholar 

  8. Liu, B.D., Lee, J.Y., Wang, H.H.: Parameter extraction and optimization for MOSFET models. Int. J. Electron. 63, 873–884 (1987)

    Article  Google Scholar 

  9. Chen, Y.-L., Wu, W.-R., Liu, C.-N.J., Li, J.C.-M.: Simultaneous optimization of analog circuits with reliability and variability for applications on flexible electronics. IEEE Trans. Comput. Aided Des. Integr. Circ. Syst. 33, 24-35 (2014)

    Google Scholar 

  10. Ling, S.H., Iu, H.H.C., Leung, F.H.F., Chan, K.Y.: Improved hybrid particle swarm optimized wavelet neural network for modelling the development of fluid dispensing for electronic packaging. IEEE Trans. Ind. Electron. 55(9), 3447–3460 (2008)

    Article  Google Scholar 

  11. Biswal, B., Dash, P.K., Panigrahi, B.K.: Power quality disturbance classification using fuzzy c-means algorithm and adaptive particle swarm optimization. IEEE Trans. Ind. Electron. 56(1), 212–220 (2009)

    Article  Google Scholar 

  12. Hong-feng, X., Guan-Zheng, T.: A novel particle swarm optimizer without velocity: Simplex-PSO. J. Cent. South Univ. 17(2), 349–356 (2010)

    Article  Google Scholar 

  13. Allen, P., Holberg, D.: CMOS Analog Circuit Design, 2nd edn. Oxford University Press, New York (2002)

    Google Scholar 

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Correspondence to R. Kar .

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Maji, K.B., Kar, R., Mandal, D., Prasanthi, B., Ghoshal, S.P. (2019). Design of Low-Voltage CMOS Op-Amp Using Evolutionary Optimization Techniques. In: Bhatia, S., Tiwari, S., Mishra, K., Trivedi, M. (eds) Advances in Computer Communication and Computational Sciences. Advances in Intelligent Systems and Computing, vol 759. Springer, Singapore. https://doi.org/10.1007/978-981-13-0341-8_24

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