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Mathematical Problems in Engineering
Volume 2012 (2012), Article ID 467402, 17 pages
Neuroendocrine-Based Cooperative Intelligent Control System for Multiobjective Integrated Control of a Parallel Manipulator
1College of Information Science and Technology, Donghua University, Shanghai 201620, China
2Engineering Research Center of Digitized Textile and Fashion Technology, Ministry of Education, Donghua University, Shanghai 201620, China
Received 7 June 2012; Accepted 1 August 2012
Academic Editor: Bo Shen
Copyright © 2012 Chongbin Guo et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- D. Zhang and Z. Gao, “Optimal kinematic calibration of parallel manipulators with pseudoerror theory and cooperative coevolutionary network,” IEEE Transactions on Industrial Electronics, vol. 59, no. 8, pp. 3221–3231, 2012.
- H. Dong, Z. Wang, and H. Gao, “Distributed filtering for a class of time-varying systems over sensor networks with quantization errors and successive packet dropouts,” IEEE Transactions on Signal Processing, vol. 60, no. 6, pp. 3164–3173, 2012.
- Z. Wang, H. Zeng, D. W. C. Ho, and H. Unbehauen, “Multiobjective control of a four-link flexible manipulator: a robust H∞ approach,” IEEE Transactions on Control Systems Technology, vol. 10, no. 6, pp. 866–875, 2002.
- B. Shen, Z. Wang, and X. Liu, “A stochastic sampled-data approach to distributed H∞ filtering in sensor networks,” IEEE Transactions on Circuits and Systems. I, vol. 58, no. 9, pp. 2237–2246, 2011.
- A. Khoukhi, “Data-driven multi-stage motion planning of parallel kinematic machines,” IEEE Transactions on Control Systems Technology, vol. 18, no. 6, pp. 1381–1389, 2010.
- Z. Sun, R. Xing, C. Zhao, and W. Huang, “Fuzzy auto-tuning PID control of multiple joint robot driven by ultrasonic motors,” Ultrasonics, vol. 46, no. 4, pp. 303–312, 2007.
- K. Pathak, J. Franch, and S. K. Agrawal, “Velocity and position control of a wheeled inverted pendulum by partial feedback linearization,” IEEE Transactions on Robotics, vol. 21, no. 3, pp. 505–513, 2005.
- M. S. Tsai, H. W. Nien, and H. T. Yau, “Development of integrated acceleration/deceleration look-ahead interpolation technique for multi-blocks NURBS curves,” International Journal of Advanced Manufacturing Technology, vol. 56, no. 5–8, pp. 601–618, 2011.
- S. Mitra and Y. Hayashi, “Bioinformatics with soft computing,” IEEE Transactions on Systems, Man, and Cybernetics Part A, vol. 36, no. 5, pp. 616–635, 2006.
- W. Savino and M. Dardenne, “Neuroendocrine control of thymus physiology,” Endocrine Reviews, vol. 21, no. 4, pp. 412–443, 2000.
- E. B. Stear, “Application of control theory to endocrine regulation and control,” Annals of Biomedical Engineering, vol. 3, no. 4, pp. 439–455, 1975.
- D. M. Keenan, J. Licinio, and J. D. Veldhuis, “A feedback-controlled ensemble model of the stress-responsive hypothalamo-pituitary-adrenal axis,” Proceedings of the National Academy of Sciences of the United States of America, vol. 98, no. 7, pp. 4028–4033, 2001.
- L. S. Farhy, “Modeling of oscillations in endocrine networks with feedback,” Methods in Enzymology, vol. 384, pp. 54–81, 2004.
- M. Neal and J. Timmis, “Timidity: a useful emotional mechanism for robot control?” Informatica, vol. 27, no. 2, pp. 197–204, 2003.
- P. Vargas, R. Moioli, L. N. d. Castro, J. Timmis, M. Neal, and F. J. V. Zuben, “Artificial homeostatic system: a novel approach,” in Advances in Artificial Life, vol. 3630 of Lecture Notes in Computer Science, pp. 754–764, 2005.
- F. M. Córdova and L. R. Cañete, “The challenge of designing nervous and endocrine systems in robots,” International Journal of Computers, Communications & Control, vol. 1, no. 2, pp. 33–40, 2006.
- B. Liu, L. Ren, and Y. Ding, “A novel intelligent controller based on modulation of neuroendocrine system,” in Proceedings of the 2nd International Symposium on Neural Networks: Advances in Neural Networks (ISNN'05), pp. 119–124, June 2005.
- Y. S. Ding and B. Liu, “An intelligent bi-cooperative decoupling control approach based on modulation mechanism of internal environment in body,” IEEE Transactions on Control Systems Technology, vol. 19, no. 3, pp. 692–698, 2011.
- D. Tang, W. Gu, L. Wang, and K. Zheng, “A neuroendocrine-inspired approach for adaptive manufacturing system control,” International Journal of Production Research, vol. 49, no. 5, pp. 1255–1268, 2011.
- C. Guo, K. Hao, Y. Ding, X. Liang, and Y. Dou, “A position-velocity cooperative intelligent controller based on the biological neuroendocrine system,” in Advances in Neural Networks—ISNN 2011, vol. 6677 of Lecture Notes in Computer Science, pp. 112–121, 2011.
- C. E. Cortés, D. Sáez, F. Milla, A. Núñez, and M. Riquelme, “Hybrid predictive control for real-time optimization of public transport systems' operations based on evolutionary multi-objective optimization,” Transportation Research Part C, vol. 18, no. 5, pp. 757–769, 2010.
- M. F. Prummel, L. J. S. Brokken, and W. M. Wiersinga, “Ultra short-loop feedback control of thyrotropin secretion,” Thyroid, vol. 14, no. 10, pp. 825–829, 2004.
- X. Liang, Y. S. Ding, L. H. Ren, K. R. Hao, H. P. Wang, and J. J. Chen, “A bioinspired multilayered intelligent cooperative controller for stretching process of fiber production,” IEEE Transactions on Systems, Man and Cybernetics Part C, vol. 42, no. 3, pp. 367–377, 2012.
- R. E. Precupa and H. Hellendoornb, “A survey on industrial applications of fuzzy control,” Computers in Industry, vol. 62, no. 3, pp. 213–226, 2011.
- H. Dong, Z. Wang, D. W. C. Ho, and H. Gao, “Robust H∞ fuzzy output-feedback control with multiple probabilistic delays and multiple missing measurements,” IEEE Transactions on Fuzzy Systems, vol. 18, no. 4, pp. 712–725, 2010.
- Z. Wang, B. Shen, H. Shu, and G. Wei, “Quantized H∞ control for nonlinear stochastic time-delay systems with missing measurements,” IEEE Transactions on Automatic Control, vol. 7, no. 6, pp. 1431–1444, 2012.
- Z. Wang, B. Shen, and X. Liu, “H∞ filtering with randomly occurring sensor saturations and missing measurements,” Automatica, vol. 48, no. 3, pp. 556–562, 2012.
- W. Shang and S. Cong, “Nonlinear computed torque control for a high-speed planar parallel manipulator,” Mechatronics, vol. 19, no. 6, pp. 987–992, 2009.
- W. Shang, S. Cong, and F. Kong, “Identification of dynamic and friction parameters of a parallel manipulator with actuation redundancy,” Mechatronics, vol. 20, no. 2, pp. 192–200, 2010.