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Variable Structure Neural Networks for Adaptive Robust Control Using Evolutionary Artificial Potential Fields Cover

Variable Structure Neural Networks for Adaptive Robust Control Using Evolutionary Artificial Potential Fields

Open Access
|Mar 2013

References

  1. [1] QIXIN, C.-YANWEN, H.-JINGLIANG, Z. : An Evolutionary Artificial Potential Field Algorithm for Dynamic Path Planning of Mobile Robot, IEEE/RSJ Int. conf. on Intelligent Robots and Systems, Beijing, Oct 2006, pp. 3331-3336.10.1109/IROS.2006.282508
  2. [2] SHI, D.-YEUNG, D. S.-GAO, J. : Sensitivity Analysis Applied to the Construction of Radial Basis Function Networks, Neural networks 18 (2005), 951-957.10.1016/j.neunet.2005.02.00615939573
  3. [3] LIU, G. P.-KADIRKAMANATHAN, V.-BILLINGS, S. A. : Variable Neural Networks for Adaptive Control of Nonlinear Systems, IEEE Trans. Trans. Syst. Man Cybern. B. Cybern. 398 No. 1 (Feb 1999), 34-43.10.1109/5326.740668
  4. [4] MEKKI, H.-CHTOUROU, M.-DERBEL, N. : Variable Structure Neural Networks for Adaptive Control of Nonlinear Systems using the Stochastic Approximation, Simulation Modeling Practice and Theory 14 (2006), 1000-1009.10.1016/j.simpat.2006.07.001
  5. [5] MEKKI, H.-CHTOUROU, M.-DERBEL, N. : A Robust Adaptive Control using Neural Network, Int. J. Modelling, Identification and control 2 No. 1 (2007).
  6. [6] LIAN, J.-LEE, Y.-SUDHOFF, S. D.-ZAK, S. H. : Variable Structure Neural Network Based Direct Adaptive Robust Control of Uncertain Systems, American Control Conference, Seattle, Washington, June 2008.10.1109/ACC.2008.4587018
  7. [7] LIAN, J.-LEE, Y.-SUDHOFF, S. D.-ZAK, S. H. : Self-Organizing Radial Basis Function Netwoek for Real-Time Approximation of Continuous-Time Dynamical Systems, IEEE Transactions on neural network, 19 No. 3 (Mar 2008).10.1109/TNN.2007.90984218334365
  8. [8] JR, J. R. B.-NICOLETTI, M. C. : A Multiclass Version of a Constructive Neural Network Algorithm Based on Linear Separability and Convex Hull, ICANN, Part II, LNCS, 2008, pp. 723-733.10.1007/978-3-540-87559-8_75
  9. [9] NORIEGA, J. R.-WANG, H. : A Direct Adaptive Neural Network Control for Unknown Nonlinear Systems and its Application, IEEE Transaction on Neural Networks 9 No. 1 (1998), 721-738.
  10. [10] SALAHSHOOR, K.-JAFARI, M. R. : On-Line Identification of Non-Linear Systems using Adaptive RBF-Based Neural Networks, International Journal of Information Science and Technology 5 No. 2 ( July/Dec 2007), 99-121.
  11. [11] AUGUSTO, L.-MELEIRO, D. C.-ZUBEN, F. J. V.-FILHO, R. M. : Constructive Learning Neural Network Applied to Identification and Control of Fuel-Ethanol Fermentation Processjour Engineering Applications of Artificial Intelligence.
  12. [12] MA, L.-KHORASANI, K. : New Training Strategies for Constructive Neural Networks with Application to Regression Problems, Neural networks 17 (2004), 589-609.10.1016/j.neunet.2004.02.00215109686
  13. [13] NICOLETTI, M. D. C.-BERTINI, J. R. : An Empirical Evaluation of Constructive Neural Network Alghorithms n classification tasks, Int. J. Innovative Computing and Application 1 No. 1, 1-13 2007.10.1504/IJICA.2007.013397
  14. [14] NICOLETTI, M. D. C. et al : Constructive Neural Network Algorithms for Feedforward Architectures Suitable for Classification Tasks, Springer-Verlag Berlin Heidelberg, SCI 258.
  15. [15] GROCHOWSKI, M.-DUCH, W. : Constructive Neural Network Algorithms that Solve Highly Non-Separable Problems, Springer-Verlag Berlin Heidelberg, SCI 258.
  16. [16] PARK, M. G.-JEON, J. H.-LEE, M. C. : Obstacle Avoidance for Mobile Robots using Artificial Potential Field Approach with Simulated Annealing, IEEE International Symposium on Industrial Electronics, vol. 3, 2001, pp. 1530-1535.
  17. [17] JAFARI, M. R.et al : On-Line Identification of Non-Linear Systems using an Adaptive RBF-based neural Network, Proceeding of WCECS, 58-3, San Francisco, Oct 2007.
  18. [18] KARAYIANNIS, N. B.-MI, G.W. : Growing Radial basis Neural Networks: Merging Supervised and Unsupervised Learning with Network Growth Techniques, IEEE Trans. Neural Netw. 8 No. 6 (Nov 1997), 1492-1506,.10.1109/72.64147118255750
  19. [19] AHANG, P. Y.-L¨U, T. S.-SONG, L. B. : Soccer Robot Path Planning Based on the Artificial Potential Field Approach with Simulated Annealing, Robotica 22 (2004), 563-566.10.1017/S0263574703005666
  20. [20] VADAKKEPAT, P.-LEE, T. H.-XIN, L. : Application of Evolutionary Artificial Potential Field in Robot Soccer System, IFSA World Congress and 20th NAFIPS int. Conf., vol. 5, Vancouver Canada, july 2001, pp. 2781-2785.
  21. [21] LEE, S.-KIL, R. M. : A Gaussian Potential Function Network with Hierachiclally Self-Organizing Learning, Neural Netw. 4 No. 2 (1996), 207-224.
  22. [22] GE, S. S.-CUI, Y. J. : New Potential Functions for Mobile Robot Path Planning, IEEE Transactions on Robotics and automation 16 No. 5 (Oct 2000), 615-620.10.1109/70.880813
  23. [23] GE, S. S.-CUI, Y. J. : New Potential Functions for Mobile Robot Path Planning, IEEE Trans. on Robot. and Auto. 16 No. 5 (Oct 2000).10.1109/70.880813
  24. [24] CHANG, W. D.-HWANG, R. C.-HSIEH, J. G. : Stable Direct Adaptive Neural Controller of Nonlinear Systems Based on Single Auto-Tuning Neuron, Neurocomputing 48 (2002), 541-554.10.1016/S0925-2312(01)00627-0
DOI: https://doi.org/10.2478/jee-2013-0001 | Journal eISSN: 1339-309X | Journal ISSN: 1335-3632
Language: English
Page range: 3 - 11
Published on: Mar 9, 2013
In partnership with: Paradigm Publishing Services
Publication frequency: 6 issues per year

© 2013 Hassen Mekki, Mohamed Chtourou, published by Slovak University of Technology in Bratislava
This work is licensed under the Creative Commons License.