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ADAPTIVE NEURAL NETWORK CONTROL OF ELECTROMAGNETIC SUSPENSION SYSTEM
Anan Suebsomran
References
[1] B.V. Jayawant, Electromagnetic suspension and levitation, IEE Review, IEE Proc, 129, 1982, 549–581.
[2] S. Banerjee, D. Prasad, and J. Pal, Design, implementation, and testing of a single axis levitation system for the suspension of a platform, ISA Transactions, 46, 2007, 239–246.
[3] S. Banerjee, T.K.S. Kumar, J. Pal, and D. Prasad, Controller design for large-gap control of electromagnetically levitated system by using an optimization technique, IEEE Transactions on Control Systems Technology, 16, 2008, 408–415.
[4] D. Cho, Y. Kato, and D. Spilman, Sliding mode and classical control magnetic levitation system, IEEE Control Systems, 13, 1993, 42–48.
[5] A. Bittar and R.M. Sales, H2 and H∞ control for MagLev system, IEEE Control System, 18, 1998, 18–25.
[6] P.K. Sinha and A.N. Pechev, Nonlinear controllers for electromagnetic suspension systems, IEEE Transactions on Automatic Control, 49, 2004, 563–568.
[7] P.H. da Rocha, H.C. Ferreira, M.C. Porsch, and R.M. Sales, Fixed-point DSP implementation of nonlinear H∞ controller for large gap electromagnetic suspension system, Control Engineering Practice, 17, 2009, 1148–1156.
[8] S.-H. Lee, Sung H.-K, J.-T. Lim, and Z. Bien, Self-tuning control of electromagnetic levitation systems, Control Engineering Practice, 8, 2000, 749–756.
[9] M.-Y. Chen, K.-N. Wu, and L.-C. Fu, Design, implementation and self-tuning adaptive control of maglev guiding system, Mechatronics, 10, 2000, 215–237.
[10] J. Kaloust, C. Ham, J. Siehling, E. Jongekryg, and Q. Han, Nonlinear robust control design for levitation and propulsion of a maglev system, IEE Proc. Control Theory Applications, 151, 2004, 460–464.
[11] P.K. Sinha and A.N. Pechev, Model reference adaptive control of a maglev system with stable maximum descent criterion, Automatica, 35, 1999, 1457–1465.
[12] S.-J. Wu, C.-T. Wu, and Y.-C. Chang, Neural–fuzzy gap control for a current/voltage – controlled 1/4 – vehicle MagLev system, IEEE Transactions on Intelligent Transportation Systems, 9, 2008, 122–136.
[13] A. Alleyne and M. Pomykalski, Control of a class of nonlinear systems subject to periodic exogenous signals, IEEE Transactions on Control Systems Technology, 8, 2000, 279–287.
[14] J.E. Slotine and W. Li, Applied nonlinear control (Englewood Cliffs, NJ: Prentice-Hall, 1991).
[15] G. Lightbody and G.W. Irwin, Nonlinear control structures based on embedded neural system models, IEEE Transactions on Neural Networks, 8, 1997, 553–567.
[16] G.P. Liu, V. Kadirkamanathan, and S.A. Billings, Variable neural networks for adaptive control of nonlinear systems, IEEE Transactions on Systems, Man, and Cybernetics – Part C: Application and Reviews, 29, 1999, 34–43.
[17] Y.-K. Choi, M.-J Lee, S. Kim, and Y.-C. Kay, Design and implementation of an adaptive neural-network compensator for control systems, IEEE Transactions on Industrial Electronics, 48, 2001, 416–423.
[18] T. Zhang and S.S. Ge, Adaptive neural network tracking control of MIMO nonlinear systems with unknown dead zones and control directions, IEEE Transactions on Neural Networks, 20, 2009, 483–497.
[19] C.-H. Wang, T.-C. Lin, T.-T. Lee, and H.-L. Liu, Adaptive hybrid intelligent control for uncertain nonlinear dynamical systems, IEEE Transactions on Systems, Man, and Cybernetics – Part B: Cybernetics, 32, 2002, 583–597.
[20] A. Rubaai, D. Ricketts, and M.D. Kankam, Development and implementation of an adaptive fuzzy-neural-network controller for brushless drives, IEEE Transactions on Industrial Electronics, 38, 2002, 441–447.
[21] F.-J. Lin and P.-H. Shen, Adaptive fuzzy-neural-network control for a DSP-based permanent magnet linear synchronous motor servo drive, IEEE Transactions on Fuzzy Systems, 14, 2006, 481–495.
[22] C.-F. Hsu, Self-organizing adaptive fuzzy neural control for a class of nonlinear systems, IEEE Transactions on Neural Networks, 18, 2007, 1232–1241.
[23] H.D. Patiño and D. Liu, Neural network-based model reference adaptive control system, IEEE Transactions on Systems, Man, and Cybernetics – Part B: Cybernetics, 30, 2000, 198–204.
[24] P.K. Sinha, Electromagnetic suspension: dynamics and control (London: Peter Peregrinus, 1987).
[25] T. Gluck, W. Kemmetmuller, C. Tump, and A. Kugi, A novel robust position estimator for self-sensing magnetic levitation systems based on least squares identification, Control Engineering Practice, 19, 2011, 146–157.
[26] J.E. Stellet, Influence of adaptation gain and reference model parameters on system performance for model reference adaptive control, World Academy of Science, Engineering and Technology, 60, 2011, 1768–1773.
[27] R.-J. Wai and J.-D. Lee, Robust levitation control for linear maglev rail system using fuzzy neural network, IEEE Transactions on Control Systems Technology, 17, 2009, 4–14.
[28] R.-J. Wai and J.-D. Lee, Backstepping-based levitation control design for linear magnetic levitation rail system, IET Control Theory Applications, 2, 2008, 72–86.
[29] S.J. Joo and J.H. Seo, Design and analysis of the nonlinear feedback linearizing control for an electromagnetic suspension system, IEEE Transactions on Control Systems Technology, 5, 1997, 135–144.
[30] Y.-K. Tzeng and T. C. Wang, A novel compensating approach for self-sensing maglev system with controlled-PM electromagnets, IEEE Transactions on Magnetics, 31, 1995, 4208–4210.
[31] Z.-J. Yang, K. Miyazaki, S. Kanae, and K. Wada, Robust position control of a magnetic levitation System via dynamic surface control technique, IEEE Transactions on Industrial Electronics, 51, 2004, 26–34.
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Abstract
DOI:
10.2316/Journal.206.2014.2.206-3728
From Journal
(206) International Journal of Robotics and Automation - 2014
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