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Optimum Design of CDM-Backstepping Control with Nonlinear Observer for Electrohydraulic Servo System Using Ant Swarm


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1. Li, X., X. Chen, C. Zhou. Combined Observer-Controller Synthesis for Electro-Hydraulic Servo System with Modeling Uncertainties and Partial State Feedback. – Journal of the Franklin Institute, Vol. 355, 2018, pp. 5893-5911.10.1016/j.jfranklin.2018.05.050Search in Google Scholar

2. Bahrami, M., M. Naraghi, M. Zareinejad. Adaptive Super-Twisting Observer for Fault Reconstruction in Electro-Hydraulic Systems. – ISA Transactions, Vol. 76, 2018, pp. 235-245.10.1016/j.isatra.2018.03.01429606494Search in Google Scholar

3. Erkan, K., B. C. Yalcın, M. Garip. Three-Axis Gap Clearance I-PD Controller Design Based on Coefficient Diagram Method for 4-Pole Hybrid Electromagnet. – Automatika, Vol. 58, 2017, No 2, pp. 147-167.10.1080/00051144.2017.1382649Search in Google Scholar

4. Arsalan, M., R. Iftikhar, I. Ahmad, A. Hasan, K. Sabahat, A. Javeria. MPPT for Photovoltaic System Using Nonlinear Backstepping Controller with Integral Action. – Solar Energy, Vol. 170, 2018, pp. 192-200.10.1016/j.solener.2018.04.061Search in Google Scholar

5. Andrade, G. A. D., R. Vazquez, D. J. Pagano. Backstepping Stabilization of a Linearized ODE-PDE Rijke Tube Model. – Automatica, Vol. 96, 2018, pp. 98-109.10.1016/j.automatica.2018.06.034Search in Google Scholar

6. Liu, Y., X. Liu, Y. Jing, S. Zhou. Adaptive Backstepping H Tracking Control with Prescribed Performance for Internet Congestion. – ISA Transactions, Vol. 72, 2018, pp. 92-99.10.1016/j.isatra.2017.10.00429079061Search in Google Scholar

7. Witkowska, A., R. Śmierzchalski. Adaptive Dynamic Control Allocation for Dynamic Positioning of Marine Vessel Based on Backstepping Method and Sequential Quadratic Programming. – Ocean Engineering, Vol. 163, 2018, pp. 570-582.10.1016/j.oceaneng.2018.05.061Search in Google Scholar

8. Vijay, M., D. Jena. Backstepping Terminal Sliding Mode Control of Robot Manipulator Using Radial Basis Functional Neural Networks. – Computers and Electrical Engineering, Vol. 67, 2018, pp. 690-707.10.1016/j.compeleceng.2017.11.007Search in Google Scholar

9. Guo, F., Y. Liu, Y. Wu, F. Luo. Observer-Based Backstepping Boundary Control for a Flexible Riser System. – Mechanical Systems and Signal Processing, Vol. 111, 2018, pp. 314-330.10.1016/j.ymssp.2018.03.058Search in Google Scholar

10. Hu, J., J. Huang, Z. Gao, H. Gu. Position Tracking Control of a Helicopter in Ground Effect Using Nonlinear Disturbance Observer-Based Incremental Backstepping Approach. – Aerospace Science and Technology, Vol. 81, 2018, pp. 167-178.10.1016/j.ast.2018.08.002Search in Google Scholar

11. Ji, N., J. Liu. Vibration Control for a Flexible Satellite with Input Constraint Based On Nussbaum Function via Backstepping Method. – Aerospace Science and Technology, Vol. 77, 2018, pp. 563-572.10.1016/j.ast.2018.03.049Search in Google Scholar

12. Herzig, N., R. Moreau, T. Redarce, F. Abry, X. Brun. Nonlinear Position and Stiffness Backstepping Controller for a Two Degrees of Freedom Pneumatic Robot. – Control Engineering Practice, Vol. 73, 2018, pp. 26-39.10.1016/j.conengprac.2017.12.007Search in Google Scholar

13. Malikov, A. I. State Observer Synthesis by Measurement Results for Nonlinear Lipschitz Systems with Uncertain Disturbances. – Automation and Remote Control, Vol. 78, 2017, No 5, pp. 782-797.10.1134/S0005117917050022Search in Google Scholar

14. Cui, M., H, Liu., W. Liu. Extended State Observer-Based Adaptive Control for a Class of Nonlinear System with Uncertainties. – Control and Intelligent Systems, Vol. 45, 2017, No 3, pp. 132-141.10.2316/Journal.201.2017.3.201-2770Search in Google Scholar

15. Dorigo, M., T. Stützle. Ant Colony Optimization. Cambridge, MIT Press, 2004.10.7551/mitpress/1290.001.0001Search in Google Scholar

16. Dorigo, M., C. Blum. Ant Colony Optimization Theory: A Survey. – Theoretical Computer Science Vol. 344, 2005, pp. 243-278.10.1016/j.tcs.2005.05.020Search in Google Scholar

17. Dorigo, M., M. Birattari, T. Stützle. Ant Colony Optimization: Artificial Ants as a Computational Intelligence Technique. – IEEE Computational Intelligence Magazine, Vol. 1, 2006, No 4, pp. 28-39.10.1109/CI-M.2006.248054Search in Google Scholar

18. Socha, K., M. Dorigo. Ant Colony Optimization for Continuous Domains – European Journal of Operational Research. Vol. 185, 2008, No 3, pp. 1155-1173.10.1016/j.ejor.2006.06.046Search in Google Scholar

19. Birattari, M., P. Pellegrini., M. Dorigo. On the Invariance of Ant Colony Optimization. – IEEE Transactions on Evolutionary Computation, Vol. 11, 2007, No 6, pp. 732-742.10.1109/TEVC.2007.892762Search in Google Scholar

20. Xiangsong, K., C. Xurui, G. Jiansheng. PID Controller Design Based on Radial Basis Function Neural Networks for the Steam Generator Level Control. – Cybernetics and Information Technologies, Vol. 16, 2016, No 5, pp. 15-26.10.1515/cait-2016-0048Search in Google Scholar

21. Kherabadi, H. A., S. E. Mood, M. M. Javidi. Mutation: A New Operator in Gravitational Search Algorithm Using Fuzzy Controller – Cybernetics and Information Technologies Vol. 17. 2017, No 1, pp. 72-86.10.1515/cait-2017-0006Search in Google Scholar

22. Roeva, O., T. Slavov, S. Fidanova. Population-Based vs. Single Point Search Meta-Heuristics for a PID Controller Tuning. – In: Handbook of Research on Novel Soft Computing Intelligent Algorithms: Theory and Practical Applications. P. Vasant, Ed. Vol. 1 and 2. IGI Global, 2014. Web 8 May 2013, pp. 200-233. DOI:10.4018/978-1-4666-4450-2, ISBN13: 9781466644502, ISBN10: 1466644508, EISBN13: 9781466644519.10.4018/978-1-4666-4450-2.ch007Search in Google Scholar

23. Roeva, O., T. Slavov. PID Controller Tuning Based on Metaheuristic Algorithms for Bioprocess Control – Biotechnology & Biotechnological Equipment, Vol. 26, 2014, No 5, pp. 3267-3277.10.5504/BBEQ.2012.0065Search in Google Scholar

24. Roeva, O., T. Slavov. A New Hybrid GA-FA Tuning of PID Controller for Glucose Concentration Control – Recent Advances in Computational Optimization, Vol. 470, 2013. pp. 155-168.10.1007/978-3-319-00410-5_9Search in Google Scholar

25. Li, J., Z. Zhongqiang, W. Yanwei, W. Xiaojing, H. Guihua, L. Shiming, D. Fatag. Research on Electro-hydraulic Force Servo System and its Control Strategy Considering Transmission Clearance and Friction. – Acta Technica, Vol. 61, 2017, No 4, pp. 207-218.Search in Google Scholar

26. Kumar, P. M., U. D. Gandhi, G. Manogaran, R. Sundarasekar, N. Chilamkurti, R. Varatharajan. Ant Colony Optimization Algorithm with Internet of Vehicles for Intelligent Traffic Control System. – Computer Networks, Vol. 144, 2018, pp. 154-162.10.1016/j.comnet.2018.07.001Search in Google Scholar

27. Mokhtari, Y., D Rekioua. High Performance of Maximum Power Point Tracking Using Ant Colony Algorithm in Wind Turbine. – Renewable Energy, Vol. 126, 2018, pp. 1055-1063.10.1016/j.renene.2018.03.049Search in Google Scholar

28. Mohammed, A. Modern Optimization Techniques for PID Parameters of Electrohydraulic Servo Control System. – International Journal on Recent and Innovation Trends in Computing and Communication, Vol. 5, 2017, No 3, pp. 71-79.Search in Google Scholar

eISSN:
1314-4081
Język:
Angielski
Częstotliwość wydawania:
4 razy w roku
Dziedziny czasopisma:
Computer Sciences, Information Technology