Open Access
MATEC Web Conf.
Volume 255, 2019
Engineering Application of Artificial Intelligence Conference 2018 (EAAIC 2018)
Article Number 04001
Number of page(s) 8
Section Logistic, Healthcare, Materials and Control
Published online 16 January 2019
  1. H.M. Omar, A. Nayfeh, Control of gantry and tower cranes, Virginia Polytech. Inst. State Univ., PhD Thesis (2003) [Google Scholar]
  2. L.A. Tuan, J.J. Kim, S.G. Lee, T.G. Lim, L.C. Nho, Second-order sliding mode control of a 3D overhead crane with uncertain system parameters, Int. J. Precis. Eng. Manuf., 15, 5, 811–819 (2014) [CrossRef] [Google Scholar]
  3. Y. Fang, E. Zergeroglu, W.E. Dixon, D.M. Dawson, Nonlinear coupling control laws for an overhead crane system, IEEE/ASME Trans. Mechatronics, 8, 3, 418–423 (2001) [CrossRef] [Google Scholar]
  4. H. Park, D. Chwa, K.-S. Hong, A feedback linearization control of container cranes: Varying rope length, Int. J. Control Autom. Syst., 5, 4, 379–387 (2007) [Google Scholar]
  5. A.S. Albert, R.B. Aswin, A fuzzy logic controller for the operation of an overhead crane control problem, Int. Res. J. Eng. Technol., 3, 7, 1420–1424 (2016) [Google Scholar]
  6. L.X. Hai, T.H. Nguyen, T.G. Khanh, N.T. Thanh, B.T. Duong, P.X. Minh, Anti-sway tracking control of overhead crane system based on PID and fuzzy sliding mode control, J. Sci. Technol., 55, 1, 116–127 (2017) [Google Scholar]
  7. J. Smoczek, J. Szpytko, Particle swarm optimization- based multivariable generalized predictive control for an overhead crane, IEEE/ASME Trans. Mechatronics, 22, 1, 258–268 (2017) [CrossRef] [Google Scholar]
  8. D.V. Diep, V.V. Khoa, PID-controllers tuning optimization with pso algorithm for nonlinear gantry crane system, Int. J. Eng. Comput. Sci., 3, 6, 6631–6635 (2014) [Google Scholar]
  9. M.I. Solihin, Wahyudi, M.A.S. Kamal, A. Legowo, Objective function selection of GA-based PID control optimization for automatic gantry crane, Int. Conf. Comput. Commun. Eng., 883–887 (2008) [Google Scholar]
  10. Y.N. Petrenko, S.E. Alavi, Fuzzy logic and genetic algorithm technique for non-linear system of overhead crane, IEEE Reg. 8 Int. Conf. Comput. Technol. Electr. Electron. Eng., 848–851 (2010) [Google Scholar]
  11. C. Pedret, R. Vilanova, R. Moreno, I. Serra, A refinement procedure for PID controllers, Electr. Eng., 88, 3, 215–221 (2006) [CrossRef] [Google Scholar]
  12. K.K. Tan, S. Huang, R. Ferdous, Robust self-tuning PID controller for nonlinear systems, J. Process Control, 12, 7, 753–761 (2002) [CrossRef] [Google Scholar]
  13. D. Valério, J.S. Da Costa, Tuning-rules for fractional PID controllers, IFAC Proc. Vol., 2, 1, 28–33 (2006) [CrossRef] [Google Scholar]
  14. Z.-L. Gaing, A particle swarm optimization approach for optimum design of PID controller in AVR system, IEEE Trans. Energy Convers., 19, 2, 384–391 (2004) [CrossRef] [Google Scholar]
  15. W.-D. Chang, J.-J. Yan, Adaptive robust PID controller design based on a sliding mode for uncertain chaotic systems, Chaos, Solitons and Fractals, 26, 1, 167–175 (2005) [CrossRef] [Google Scholar]
  16. W. Xiuli, W. Yongji, Z. Hui, H. Xiaoyong, PSO- PID: A Novel controller for AQM routers, IFIP Int. Conf. Wirel. Opt. Commun. Networks, 1–5 (2006) [Google Scholar]
  17. W.A.W. Azhar, M. Nafrizuan, S. Azlyna, Tuning of optimum PID Controller parameter using particle swarm optimization algorithm approach, National Conf. Software Eng. Comput. Syst, 1–7 (2007) [Google Scholar]
  18. R. Poli, J. Kennedy, T. Blackwell, Particle swarm optimization, Swarm Intell., 1, 1, 33–57 (2007) [CrossRef] [Google Scholar]
  19. Y. Shi, R.C. Eberhart, A modified particle swarm optimizer, 1998 IEEE Int. Conf. Evol. Comput. Proc. IEEE World Congr. Comput. Intell. (Cat. No.98TH8360), 69–73 (1998) [Google Scholar]
  20. Q. Bai, Analysis of particle swarm optimization algorithm, Comput. Inf. Sci., 3, 1, 180–184 (2010) [Google Scholar]
  21. Y. Shi, R.C. Eberhart, Particle swarm optimization: developments, applications and resources, Proc. 2001 Congr. Evol. Comput. (IEEE Cat. No.01TH8546), 1, 81–86 (2001) [CrossRef] [Google Scholar]
  22. R.C. Eberhart, J. Kennedy, A new optimizer using particle swarm theory, MHS’95. Proc. Sixth Int. Symp. Micro Machine Human Sci., 39–43 (1995) [Google Scholar]
  23. M.I. Solihin, Wahyudi, M.A.S. Kamal, A. Legowo, Optimal PID controller tuning of automatic gantry crane using PSO algorithm, 2008 5th Int. Symp. Mechatronics its Appl., 25–29 (2008) [Google Scholar]

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