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Linked References

1. A. M. Prokhorenkov and A. S. Sovlukov, “Fuzzy models in control systems of boiler aggregate technological processes,” Computer Standards & Interfaces, vol. 24, no. 2, pp. 151–159, 2002. View at Publisher · View at Google Scholar
2. M. J. Er and Y. L. Sun, “Hybrid fuzzy proportional-integral plus conventional derivative control of linear and nonlinear systems,” IEEE Transactions on Industrial Electronics, vol. 48, no. 6, pp. 1109–1117, 2001. View at Publisher · View at Google Scholar
3. R. K. Mudi and N. R. Pal, “A robust self-tuning scheme for PI- and PD-type fuzzy controllers,” IEEE Transactions on Fuzzy Systems, vol. 7, no. 1, pp. 2–16, 1999. View at Publisher · View at Google Scholar
4. M. Abd El-Geliel and M. A. El-Khanzendar, “Supervisory fuzzy logic controller used for process loop control in DCS system,” in Proceedings of the IEEE Conference on Control Applications (CCA '03), vol. 1, pp. 263–268, Istanbul, Turkey, June 2003.
5. A. Abdennour, “An intelligent supervisory system for drum type boilers during severe disturbances,” International Journal of Electrical Power & Energy System, vol. 22, no. 5, pp. 381–387, 2000. View at Publisher · View at Google Scholar
6. L. Reznik, O. Ghanayem, and A. Bourmistrov, “PID plus fuzzy controller structures as a design base for industrial applications,” Engineering Applications of Artificial Intelligence, vol. 13, no. 4, pp. 419–430, 2000. View at Publisher · View at Google Scholar
7. A. Visioli, “Fuzzy logic based set-point weight tuning of PID controllers,” IEEE Transactions on Systems, Man, and Cybernetics A, vol. 29, no. 6, pp. 587–592, 1999. View at Publisher · View at Google Scholar
8. M. Das, A. Banerjee, R. Ghosh, et al., “A study on multivariable process control using message passing across embedded controllers,” ISA Transactions, vol. 46, no. 2, pp. 247–253, 2007. View at Publisher · View at Google Scholar · View at PubMed
9. S. X. Yang, H. Li, M. Q.-H. Meng, and P. X. Liu, “An embedded fuzzy controller for a behavior-based mobile robot with guaranteed performance,” IEEE Transactions on Fuzzy Systems, vol. 12, no. 4, pp. 436–446, 2004. View at Publisher · View at Google Scholar
10. F. Thomas, M. M. Nayak, S. Udupa, J. K. Kishore, and V. K. Agrawal, “A hardware/software codesign for improved data acquisition in a processor based embedded system,” Microprocessors and Microsystems, vol. 24, no. 3, pp. 129–134, 2000. View at Publisher · View at Google Scholar
11. E. Suwartadi, C. Gunawan, A. Setijadi, and C. Machbub, “First step toward internet based embedded control system,” in Proceedings of the 5th Asian Control Conference, vol. 2, pp. 1226–1231, Melbourne, Australia, July 2004.
12. Y. Majanne, “Model predictive pressure control of steam networks,” Control Engineering Practice, vol. 13, no. 12, pp. 1499–1505, 2005. View at Publisher · View at Google Scholar
13. W. Jian and C. Wenjian, “Development of an adaptive neuro-fuzzy method for supply air pressure control in HVAC system,” in Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, vol. 5, pp. 3806–3809, Nashville, Tenn, USA, October 2000. View at Publisher · View at Google Scholar
14. G. Nygaard and G. Nævdal, “Nonlinear model predictive control scheme for stabilizing annulus pressure during oil well drilling,” Journal of Process Control, vol. 16, no. 7, pp. 719–732, 2006. View at Publisher · View at Google Scholar
15. J. C. Gelin, C. Labergére, and S. Thibaud, “Modeling and process control for the hydroformig of metallic liners used for hydrogen storage,” Journal of Materials Processing Technology, vol. 177, no. 1–3, pp. 697–700, 2006. View at Publisher · View at Google Scholar
16. N. Kanagaraj and P. Sivashanmugam, “An embedded fuzzy controller for real time pressure control,” in Proceedings of the IEEE International Conference on Industrial Technology (ICIT '06), pp. 2023–2027, Mumbai, India, December 2006. View at Publisher · View at Google Scholar
17. S. Paramasivam and R. Arumugam, “Hybrid fuzzy controller for speed control of switched reluctance motor drives,” Energy Conversion and Management, vol. 46, no. 9-10, pp. 1365–1378, 2005. View at Publisher · View at Google Scholar
18. R. Ketata, D. De Geest, and A. Titli, “Fuzzy controller: design, evaluation, parallel and hierarchical combination with a PID controller,” Fuzzy Sets and Systems, vol. 71, no. 4, pp. 113–129, 1997. View at Publisher · View at Google Scholar · View at MathSciNet
19. S.-Z. He, S. Tan, F.-L. Xu, and P.-Z. Wang, “Fuzzy self-tuning of PID controllers,” Fuzzy Sets and Systems, vol. 56, no. 1, pp. 37–46, 1993. View at Publisher · View at Google Scholar · View at MathSciNet
20. A. Visioli, “Tuning of PID controllers with fuzzy logic,” IEE Proceedings: Control Theory and Applications, vol. 148, no. 1, pp. 1–8, 2001. View at Publisher · View at Google Scholar
21. H.-J. Cho, K.-B. Cho, and B.-H. Wang, “Fuzzy-PID hybrid control: automatic rule generation using genetic algorithms,” Fuzzy Sets and Systems, vol. 92, pp. 305–316, 1997. View at Publisher · View at Google Scholar · View at MathSciNet
22. P. Sivashanmugam, N. Kanagaraj, and R. Kumar, “Real time rate of change of pressure measurement and pressure control,” Journal of Scientific and Industrial Research, vol. 66, no. 2, pp. 120–123, 2007.
23. K. M. Passino and Y. Stephen, Fuzzy Control, Addison-Wesley Longman, Menlo Park, Calif, USA, 1998.
24. 2003, PHYTECH-AT91M55800A Hardware Manual, PHYTECH Technology Holding Company.