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Real-time embedded emotional controller

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Abstract

Recent studies show that emotion is a mechanism for fast decision-making in human and other animals. Mathematical models have been developed for describing emotion in mammals. These models, similar to other bioinspired models, must be implemented in embedded platforms for industrial and real applications. In this paper, brain emotional learning based intelligent controller, which is based on mammalian middle brain, is designed and implemented on field-programmable gate arrays, and this emotional controller is applied for controlling of laboratorial overhead traveling crane in model-free and embedded manner. The main features of this controller are leaning capability, providing a model-free control algorithm, robustness and the ability to respond swiftly. By designing appropriate stress signals, a designer can implement a proper trade among control objectives.

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Notes

  1. The digital pendulum control system, crane system, manufactured by Feedback Instruments Limited, England.

References

  1. Tyrrell AM, Sanchez E, Floreano E, Tempesti E, Mange E, Moreno JM, Rosenberg J, Villa A (2003) POEtic Tissue: an integrated architecture for bio-inspired hardware from biology to hardware. In: Proceedings of the 5th international conference on evolvable systems (ICES′03), LNCS 2606. Springer, Berlin, pp 129–140

  2. Teodorescu HN, Jain LC (2001) Hardware implementation of intelligent systems. Physica, Heidelberg. ISBN:3-7908-1399-0

  3. Jamali MR, Valadbeigi M, Dehyadegari M, Navabi M, Lucas C (2007) Toward embedded emotionally intelligent system. In: Fifth IEEE east–west design and test international symposium, Jereven, Armenia, 7–10 September 2007, pp 51–56

  4. Moren J (2002) Emotion and learning: a computational model of the amygdale. PhD thesis, Lund university, Lund, Sweden

  5. Pedram A, Jamali MR, Pedram T, Fakhraie SM, Lucas C (2006) Local linear model tree (LOLIMOT) reconfigurable parallel hardware. Trans Eng Comput Technol Pol 13:96–101

    Google Scholar 

  6. Fakhraie SM, Smith KC (1997) VLSI-compatible implementations for artificial neural networks. Kluwer, Norwell

    MATH  Google Scholar 

  7. Reyneri LM (1998) Neuro-fuzzy hardware: design, development and performance. In: Proceedings of FEPPCON III, Skukuza, South Africa, 12–15 July 1998

  8. Pedram A, Jamali MR, Fakhraie SM, Lucas C (2006) Reconfigurable parallel hardware for computing local linear neuro-fuzzy model. In: Proceedings of PARELEC 2006, Bialystok, Poland, 13–17 September 2006, pp 198–201

  9. Reyneri LM (2003) Implementation issues of neuro-fuzzy hardware: going toward hw/sw codesign. IEEE Trans Neural Networks 14(1):176–194

    Article  Google Scholar 

  10. Balkenius C, Moren J (1998) A computational model of emotional conditioning in the brain. In: Workshop on grounding emotions in adaptive systems, Zurich, 21 August 1998

  11. Moren J, Balkenius J (2000) A computational model of emotional learning in the amygdala: from animals to animals. In: Sixth international conference on the simulation of adaptive behavior. MIT Press, Cambridge, pp 383–391

  12. Lucas C, Shahmirzadi D, Sheikholeslami N (2004) Introducing BELBIC: brain emotional learning based intelligent controller. Int J Intell Automat Soft Comput 10(1):11–22

    Google Scholar 

  13. Milasi RM, Lucas C, Araabi BN (2004) Speed control of an interior permanent magnet synchronous motor using BELBIC (Brain Emotional Learning Based Intelligent Controller). In: Special session on emotional learning and decision fusion in satisficing control and information processing. Minisymposium on satisficing, multiagent, and cyberlearning systems, Fifth international symposium on intelligent automation and control, ISIAC 116, world automation congress, WAC 2004. Seville, Spain, June 28– July 1, 2004

  14. Sheikholeslami N, Shahmirzadi D, Semsar E, Lucas C, Yazdanpanah MJ (2006) Applying brain emotional learning algorithm for multivariable control of HVAC systems. Int J Intell Fuzzy Syst 17(1):35–46

    Google Scholar 

  15. Rouhani H, Jalili Kharaajoo M, Araabi BN, Eppler W, Lucas C (2007) Brain emotional learning based intelligent controller applied to neurofuzzy model of micro heat exchanger. Expert Syst Appl 32(3):911–918

    Article  Google Scholar 

  16. Milasi RM, Lucas C, Araabi BN (2006) Intelligent modeling and control of washing machine using locally linear neuro-fuzzy (LLNF) modeling and modified brain emotional learning based intelligent controller (BELBIC). Asian J Control 8(4):393–400

    Google Scholar 

  17. Milasi RM, Jamali MR, Lucas C (2007) Intelligent washing machine: a bio-inspired and multi-objective approach. Int J Control Automat Syst 5(4):436–443

    Google Scholar 

  18. Jamali MR, Pedram A, Milasy MR, Lucas C (2006) Design and implementation of BELBIC pattern. In: Proceedings of 14th Iranian conference on electrical engineering, ICEE2006, Teheran, May 2006

  19. Alexander C (1979) The timeless way of building. Oxford University Press, New York

  20. Pouladzadeh P, Jamali SM, Lucas C (2007) Emotional control of automotive suspension system. In: Proceedings of sixth international CSIT conference, Yerevan, Armenia, 24–28 September 2007, pp 155–158

  21. Milasi RM, Lucas C, Arrabi BN, Radwan TS, Rahman MA (2006) Implementation of emotional controller for interior permanent magnet synchronous motor drive. In: IEEE/IAS 41st annual meeting: industry applications, Tampa, 8–12 October 2006

  22. Jamali MR, Arami A, Hosseini B, Moshiri B, Lucas C (2008) Real time emotional control for anti-swing and positioning control of SIMO overhead traveling crane. Int J Innovat Comput Informat Control 4(9):2333–2344

    Google Scholar 

  23. Mange D, Sipper M, Stauffer A, Tempesti G (2000) Towards robust integrated circuits: the embryonics approach. Proc IEEE 88(4):516–541

    Article  Google Scholar 

  24. Yager RR (1991) An alternative procedure for the calculation of fuzzy logic controller values. J Jpn Soc Fuzzy Technol 3:736–746

    MathSciNet  Google Scholar 

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Correspondence to M. R. Jamali.

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Jamali, M.R., Dehyadegari, M., Arami, A. et al. Real-time embedded emotional controller. Neural Comput & Applic 19, 13–19 (2010). https://doi.org/10.1007/s00521-008-0227-x

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