Open Access
Issue |
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 | |
DOI | https://doi.org/10.1051/matecconf/201925504001 | |
Published online | 16 January 2019 |
- H.M. Omar, A. Nayfeh, Control of gantry and tower cranes, Virginia Polytech. Inst. State Univ., PhD Thesis (2003) [Google Scholar]
- 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]
- 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]
- 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]
- 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]
- 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]
- 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]
- 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]
- 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]
- 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]
- C. Pedret, R. Vilanova, R. Moreno, I. Serra, A refinement procedure for PID controllers, Electr. Eng., 88, 3, 215–221 (2006) [CrossRef] [Google Scholar]
- 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]
- D. Valério, J.S. Da Costa, Tuning-rules for fractional PID controllers, IFAC Proc. Vol., 2, 1, 28–33 (2006) [CrossRef] [Google Scholar]
- 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]
- 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]
- 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]
- 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]
- R. Poli, J. Kennedy, T. Blackwell, Particle swarm optimization, Swarm Intell., 1, 1, 33–57 (2007) [CrossRef] [Google Scholar]
- 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]
- Q. Bai, Analysis of particle swarm optimization algorithm, Comput. Inf. Sci., 3, 1, 180–184 (2010) [Google Scholar]
- 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]
- 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]
- 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]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.