[1] C. C. L. Lynch, and M. R. Popovic, “Closed-Loop Control for FES: Past Work and Future Directions”, 10th Annual Conference of the International FES Society, Ottawa, Canada, pp. 56-59, (2005).
[2] S. Bin Mohamed Ibrahim, “The PID Controller Design Using Particle swarm optimization Algorithm”, PhD thesis, University of Southern Queensland, Toowoomba, Australia, pp.132-137, (2005).
[3] D. Blana, E.K. Chadwick, A. Bogert and R. F. Kirsch, “Feedback Control for a High Level Upper Extremity Neuroprosthesis”, ASB 29th Annual Meeting, Cleveland, Ohio, pp. 28-33, (2005).
[4] C. L. Lynch and M. R. Popovic, “Functional Electrical Stimulation”, IEEE Control Systems MaGAzine, Cleveland, Ohio, (2008).
[5] D. Blana, R. F. Kirsch and E. K. Chadwick, “Combined Feed forward and Feedback Control of a Redundant, Nonlinear, Dynamic Musculoskeletal System”, International Federation for Medical and Biological Engineering, Vol. 47, No. 5, pp. 533-542, (2009).
[6] M. Ferrarin, F. Palazzo, R. Riener and J. Quintern, “Model-Based Control of FESInduced Single Joint Movements”, IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol. 9, No. 3. pp. 78-88, (2001).
[7] V. M. Zatsiorsky, “Kinetics of Human Motion”, Human Kinetics, New Zealand, pp. 265-350, (2002).
[8] D. Zhang, and W. T. Ang, “Tremor Suppression of Elbow Joint via Functional Electrical Stimulation: A Simulation Study”, Proceeding of the 2006 IEEE, International Conference on Automation Science and Engineering, Beijing, China, pp.76-81 (2006).
[9] A. Maleki and R. Shafaei, “Musculoskeletal Model of Arm for FES Research Studies”, 4th Cario International Biomedical Conference, University of Salford, Ireland UK, (2008).
[10] Negin Hesam-Shariati, “Control of Reanimation of Paralyzed Arm for Reaching Movement Using FES’’, M. Sc. Thesis, Bioelectrics, Amirkabir University of Technology, 183 pages, (2012).
[11] K. Kurosawa, R. Futami, T. Watanabe and N. Hoshimiya, “Joint Angle Control by FES Using a Feedback Error Learning Controller”, IEEE Transactions on Neural Systems and Rehabilitation *Corresponding author email address: mhbayati88@gmail.com Engineering, Vol. 13, No. 3, pp. 62-77, (2005).
[12] M. O. Ali, S. P. Koh, K. H. Chong, S. K. Tiong and Z.A. Obaid, "Genetic Algorithm Tuning Based PID Controller for Liquid-Level Tank System", Proceedings of the International Conference on Man- Machine Systems (ICoMMS), Kuala Lumpur, Malaysia, pp. 29-33 (2009).
[13] Eberhart R, and J. Kennedy, A New Optimizer Using Particle Swarm Theory. Proc of 6th International Symposium on Micro Machine and Human Science, Nagoya, Japan. IEEE Service Center Piscataway NJ, pp. 39-43, (1995).
[14] J. Kennedy, R. Eberhart, Particle Swarm Optimization. Proc of IEEE International Conference on Neural Network, Perth, Australia, IEEE Service Center Piscataway NJ, pp. 1942-1948, (1995).
[15] M. Clerc, and J. Kennedy, The particle swarm-explosion stability, and convergence in a multidimensional complex space. IEEE Transactions on Evolutionary Computation, Vol. 6, No. 1, pp. 58-73, (2002).
[16] M. Dorigo, V. Maniezzo, and A. Colorni, Ant system: optimization by a colony of cooperationg agents. IEEE Transactions on Systems. Man, and Cybernetics-Part B, Vol. 26, No. 1, pp. 29-41, (1996).
[17] Y. Shi, and R. C. Eberhart, A modified particle swam optimizer. IEEE Word Congress on Computational Intelligence, pp. 69-73, (1998).
[18] Zheng Jianchao, Jie Jing, and Cui Zhihua., Particle swam optimization. Science Publishing Company of Beijing. Vol. 22, No. 3, pp. 94-112 (2004).
[19] R. C. Eberhart, and Y. Shi, Comparison between genetic algorithms and Particle Swarm Optimization. Porto V W, Saravanan N, Waagen D, et al. Evolutionary Programming VII. [S.l.]: Springer, pp. 611-616, (1998).
[20] R. C. Eberhart, and Y. Shi, Comparing inertia weights and constriction factors in Particle Swarm Optimization. Proceedings of the Congress on Evolutionary Computation, pp. 84-88, (2000).
[21] N. Higashi, and H. Iba, Particle Swarm Optimization with Gaussian mutation. Proceedings of the 2003 Congress on Evolutionary Computation. Piscataway, NJ: IEEE Press, pp. 72-79, (2003).
[22] M. Clerc, The swarm and the queen: towards a deterministic and adaptive particle swarm optimization. Proceedings of the Congress on Evolutionary Computation. Piscataway, NJ: IEEE Service Center, pp. 1951-1957, (1999).
[23] A. Colorni, M. Dorigo, and V. Maniezzo, et al.; Distributed optimization by ant colonies. Proceedings of the 1st European Conference on Artificial Life, pp. 134- 142, (1991).
[24] P. J. Angeline, Using selection to improve Particle Swarm Optimization. Proceedings of the Congress on Evolutionary Computation. Piscataway. NJ: IEEE Press, pp. 84-89, (1999).
[25] Duan Haibin, Ant Colony Optimization theory and Application. Science Publishing Company of Beijing. Vol. 23, No. 1, pp. 82-93 (2005).
[26] Gao Ying, Xie Shengli, Particle swam optimization Algorithm based on simulated annealing (SA) approach .Computer Engineering and Application, Vol. 40, No. 1, pp. 47-49, (2004).
[27] Qinghai Bai, Analysis of Particle Swarm Optimization Algorithm ‘Journal of Computer and Information Science’, Vol. 3, No. 1, pp. 57-71, (2010).
[28] Chen Yonggang, Yang Fengjie, and Sun Jigui.; A new Particle swam optimization Algorithm. Journal of Jilin University, Vol. 24, No. 2, pp. 181-185, (2006).
Send comment about this article