DOI QR코드

DOI QR Code

An intelligent fuzzy theory for ocean structure system analysis

  • Chen, Tim (Faculty of Information Technology, Ton Duc Thang University) ;
  • Cheng, C.Y.J. (Faculty of Engineering, King Abdulaziz University) ;
  • Nisa, Sharaban Tahura (ECE Department, Carnegie Mellon University) ;
  • Olivera, Jonathan (School of Computer Science University of Nottingham Jubilee Campus)
  • Received : 2018.10.11
  • Accepted : 2019.03.16
  • Published : 2019.06.25

Abstract

This paper deals with the problem of the global stabilization for a class of ocean structure systems. It is well known that, in general, the global asymptotic stability of the ocean structure subsystems does not imply the global asymptotic stability of the composite closed-loop system. The classical fuzzy inference methods cannot work to their full potential in such circumstances because given knowledge does not cover the entire problem domain. However, requirements of fuzzy systems may change over time and therefore, the use of a static rule base may affect the effectiveness of fuzzy rule interpolation due to the absence of the most concurrent (dynamic) rules. Designing a dynamic rule base yet needs additional information. In this paper, we demonstrate this proposed methodology is a flexible and general approach, with no theoretical restriction over the employment of any particular interpolation in performing interpolation nor in the computational mechanisms to implement fitness evaluation and rule promotion.

References

  1. Azevedo, A. and Rezende, S.M. (1991), "Controlling chaos in spin-wave instabilities", Phys. Rev. Lett., 66, 1342-1345. https://doi.org/10.1103/PhysRevLett.66.1342
  2. Buss, M. and Hashimoto, H. (1996), "Intelligent control for human-machine systems", IEEE-ASME Transactions on Mechatronics, 1, 50-55. https://doi.org/10.1109/3516.491409
  3. Chang, J.F., Tsai, P.W., Chen, J.F. and Hsiao, C.T. (2014a), "The comparison between IABC with EGARCH in foreign exchange rate forecasting", Proceedings of the 1st Euro-China Conference on Intelligent Data Analysis and Applications, Shenzhen, China, June.
  4. Chang, J.F., Yang, T.W. and Tsai, P.W. (2014), "Stock portfolio construction using evolved bat algorithm", Proceedings of the 27th International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems, Kaohsiung, Taiwan, June.
  5. Cheng, S.H., Chen, S.M. and Chen, C.L. (2016), "Weighted fuzzy interpolative reasoning for sparse fuzzy rule-based systems based on piecewise fuzzy entropies of fuzzy sets", Inf. Sci., 329, 503-523. https://doi.org/10.1016/j.ins.2015.09.035
  6. Chu, S.C. and Tsai, P.W. (2007), "Computational intelligence based on behaviors of cats", Int. J. Innov. Comput. Inform. Control, 3(1), 163-173.
  7. Chu, S.C., Tsai, P.W. and Pan, J.S. (2006), "Cat Swarm optimization", Proceedings of the Trends in Artificial Intelligence, 9th Pacific Rim International Conference on Artificial Intelligenc, Guilin, China.
  8. Colet, P. and Braiman, Y. (1996), "Control of chaos in multimode solid state lasers by the use o small periodic perturbations", Phys. Rev. E, 53, 200-206. https://doi.org/10.1103/PhysRevE.53.200
  9. Desoer, C.A. and Shahruz, S.M. (1986), "Stability of the dithered nonlinear system with backlash or hysteresis", Int. J. Control, 43, 1045-1060. https://doi.org/10.1080/00207178608933522
  10. Eberhart, R. and Kennedy, J. (1995), "A new optimizer using particle swarm theory", Proceedings of the 6th International Symposium on Micro Machine and Human Science.
  11. Egresits, C., Monostori, L. and Hornyak, J. (1998), "Multistrategy learning approaches to generate and tune fuzzy control structures and their application in manufacturing", J. Intel. Manufact., 9, 323-329. https://doi.org/10.1023/A:1008922709029
  12. Gauthier, D.J., Sukow, D.W., Concannon, H.M.and Socolar, J.E.S. (1994), "Stabilizing unstable periodic orbits in a fast diode resonator using continuous time-delay autosynchronization", Phys. Rev. E, 50, 2343-2346. https://doi.org/10.1103/PhysRevE.50.2343
  13. Grauel, A., Ludwig, L.A. and Klene, G. (1997), "Comparison of different intelligent methods for process and quality monitoring", Int. J. Approx. Reason., 16, 89-117. https://doi.org/10.1016/S0888-613X(97)87368-9
  14. Hammami, M.A. (2001), "Global convergence of a control system by means of an observer", J. Optim. Theory Appl., 108, 377-388. https://doi.org/10.1023/A:1026442402201
  15. Harris, D.C. (2007), Quantitative Chemical Analysis, (7th Ed.), W.H. Freeman and Company, New York, NY, USA.
  16. Harris, D.C. (2007), Quantitative Chemical Analysis, W.H. Freeman and Company, New York, NY, USA.
  17. Hu, Q. (2008), "Sliding mode maneuvering control and active vibration damping of three-axis stabilized flexible spacecraft with actuator dynamics", Nonlinear Dynam., 52, 227-248. https://doi.org/10.1007/s11071-007-9274-6
  18. Hwang C.C., Chow, H.Y. and Wang, Y.K. (1996), "A new feedback control of a modified Chua's circuit system", Physica D, 92, 95-100. https://doi.org/10.1016/0167-2789(95)00276-6
  19. Ignaciuk, P. and Bartoszewicz, A. (2010). "Linear-quadratic optimal control strategy for periodic-review inventory systems", Automatica, 46(12), 1982-1993. https://doi.org/10.1016/j.automatica.2010.09.010
  20. Jankovic, M., Sepulchre, R. and Kokotovic, P.V. (1996), "Constructive Lyapunov stabilisation of nonlinear cascade systems", IEEE T. Autom. Control, 41, 1723-1735. https://doi.org/10.1109/9.545712
  21. Jose, A.R. (1994), "Nonlinear feedback for controlling the Lorenz equation", Phys. Rev. E, 50, 2339-2342,
  22. Kapitaniak, T., Kocarev, L.J. and Chua, L. O. (1993), "Controlling chaos without feedback and control signals", Int. J. Bifurcation Chaos, 3, 459-468. https://doi.org/10.1142/S0218127493000362
  23. Karaboga, D. (2005), An Idea Based On Honey Bee Swarm For Numerical Optimization. Technical Report-TR06, Erciyes University, Engineering Faculty, Computer Engineering Department.
  24. Karaboga, D. and Basturk, B. (2008), "On the performance of artificial bee colony (ABC) algorithm", Appl. Soft Comput., 8(1), 687-697. https://doi.org/10.1016/j.asoc.2007.05.007
  25. Kawamoto, S., Tada, K., Ishigame, A. and Taniguchi, T. (1992a), "An approach to stability analysis of second order fuzzy systems", Proceedings of the IEEE International Conference on Fuzzy Systems, San Diego, CA.
  26. Kawamoto, S., Tada, K., Onoe, N., Ishigame, A. and Taniguchi, T. (1992), "Construction of exact fuzzy system for nonlinear system and its stability analysis", Proceedings of the 8th Fuzzy System Symposium, Hiroshima, Japan.
  27. Korkmaz, S. (2011), "A review of active structural control: challenges for engineering informatics", Comput. Struct., 89(23),: 2113-2132. https://doi.org/10.1016/j.compstruc.2011.07.010
  28. Kuo, R.J. and Xue, K.C. (1998), "An intelligent sales forecasting system through integration of artificial neural network and fuzzy neural network", Comput. Ind., 37, 1-15. https://doi.org/10.1016/S0166-3615(98)00066-9
  29. Kuok, S.C. and Yuen, K.V. (2012), "Structural health monitoring of Canton tower using Bayesian framework", Smart Struct. Syst., 10(4-5), 375-391. https://doi.org/10.12989/sss.2012.10.4_5.375
  30. Lam, H.K. (2009), "Stability analysis of T-S fuzzy control systems using parameter-dependent Lyapunov function", IET Control Theory Appl., 3, 750-762. https://doi.org/10.1049/iet-cta.2008.0196
  31. Lee, H.H. and Juang, H.H. (2012), "Experimental study on the vibration mitigation of offshore tension leg platform system with UWTLCD", Smart Struct. Syst., 9(1), 71-104. https://doi.org/10.12989/sss.2012.9.1.071
  32. Lee, H.J., Park, J.B. and Chen, G. (2001), "Robust fuzzy control of nonlinear systems with parameter uncertainties", IEEE T. Fuzzy Syst., 9, 369-379. https://doi.org/10.1109/91.919258
  33. Lewandowski, R., Bartkowiak, A. and Maciejewski, H. (2012), "Dynamic analysis of frames with viscoelastic dampers: a comparison of damper models", Struct. Eng. Mech., 41(1), 113-137. https://doi.org/10.12989/sem.2012.41.1.113
  34. Lian, S.T., Marzuki, K. and Rubiyah, Y. (1998), "Tuning of a neuro-fuzzy controller by genetic algorithms with an application to a coupled-tank liquid-level control system", Eng. Appl. Artif. Intel., 11, 517-529. https://doi.org/10.1016/S0952-1976(98)00012-8
  35. Liu, S.C. and Lin, S.F. (2012), "LMI-based robust sliding control for mismatched uncertain nonlinear systems using fuzzy models", Int. J. Robust Nonlinear Control, 22(16), 1827-1836. https://doi.org/10.1002/rnc.1789
  36. Liu, S.C. and Lin, S.F. (2012a), "LMI-based robust adaptive control for mismatched uncertain nonlinear time-delay systems using fuzzy models", Proceedings of the 2012 International symposium on Computer, Consumer and Control, Taichung, Taiwan.
  37. Liu, S.C. and Lin, S.F. (2013), "Robust sliding control for mismatched uncertain fuzzy time-delay systems using linear matrix inequality approach", J. Chinese Inst. Engineers, 36(5), 589-597. https://doi.org/10.1080/02533839.2012.734557
  38. Liu, X. and Zhang, Q. (2003), "New approach to H1 controller designs based on fuzzy observers for T-S fuzzy systems via LMI", Automatica, 39, 1571-1582. https://doi.org/10.1016/S0005-1098(03)00172-9
  39. Liu, Y.J. and Li, Y.X. (2010), "Adaptive fuzzy output-feedback control of uncertain SISO nonlinear systems", Nonlinear Dyn., 61, 749-761. https://doi.org/10.1007/s11071-010-9684-8
  40. Loria, A. and Nesic, D. (2003), "On uniform boundedness of parametrized discrete-time systems with decaying inputs: applications to cascades", Syst. Control Lett., 94, 163-174.
  41. Ma, X.J. and Sun, Z.Q. (2001), "Analysis and design of fuzzy reduceddimensional observer and fuzzy functional observer", Fuzzy Set. Syst., 120, 35-63. https://doi.org/10.1016/S0165-0114(99)00145-1
  42. Ma, X.J., Sun, Z.Q. and He, Y. Y. (1998), "Analysis and design of fuzzy controller and fuzzy observer", IEEE T. Fuzzy Syst., 6, 41-51. https://doi.org/10.1109/91.660807
  43. May, M. (1976),, "Simple mathematical models with very complicated dynamics", Nature, 261, 459-467. https://doi.org/10.1038/261459a0
  44. Mazenc, F., Sepulchre, R. and Jankovic, M. (1999), "Lyapunov functions for stable cascades and applications to stabilization", IEEE T. Automat. Contr., 44, 1795-1800. https://doi.org/10.1109/9.788556
  45. Mossaheb, S. (1983), "Application of a method of averaging to the study of dithers in nonlinear systems", Int. J. Contr., 38, 557-576.. https://doi.org/10.1080/00207178308933094
  46. Narendra, K.G., Khorasani, K., Sood, V.K., et al. (1998), "Intelligent current controller for an HVDC transmission link", IEEE T. Power Syst., 13, 1076-1083. https://doi.org/10.1109/59.709102
  47. Necasek, J.; Vaclavik, J. and Marton, P. (2016), "Digital synthetic impedance for application in vibration damping", Rev. Sci. Instrum., 87, 024704. 28.
  48. Ott, E., Grebogi, D. and Yorke, J. A. (1990), "Controlling chaos", Phys. Rev. Lett., 64, 1196-1199 (1990). https://doi.org/10.1103/PhysRevLett.64.1196
  49. Panda, G., Pardhan, P.M., and Majhi, B. (2011), "IIR system identification using cat swarm optimization", Expert. Syst. Appl., 38, 12671-12683. https://doi.org/10.1016/j.eswa.2011.04.054
  50. Panteley, E. and Loria, A. (1998), "On global uniform asymptotic stability of nonlinear time-varying non autonomous systems in cascade", Syst. Control Lett., 33, 131-138. https://doi.org/10.1016/S0167-6911(97)00119-9
  51. Pardhan, P.M. and Panda, G. (2012), "Solving multiobjective problems using cat swarm optimization", Exp. Syst. Appl., 39, 2956-2964. https://doi.org/10.1016/j.eswa.2011.08.157
  52. Park, J., Kim, J. and Park, D. (2003), "LMI-based design of stabilizing fuzzy controllers for nonlinear systems described by Takagi-Sugeno fuzzy model", Fuzzy Set. Syst., 122, 73-82.
  53. Perez-Diaz, J., Valiente-Blanco, I. and Cristache, C.Z. (2016), "Damper: A new paradigm for attenuation of vibrations", Machines, 4, 12, doi:10.3390/machines4020012. 34. https://doi.org/10.3390/machines4020012
  54. Sciortino, J.C. (1997), "Autonomous ESM systems", Naval Engineers J., 9, 73-84.
  55. Seibert, P. and Suarez, R. (1990), "Global stabilisation of nonlinear cascade systems", Syst. Control Lett., 14, 347-352. https://doi.org/10.1016/0167-6911(90)90056-Z
  56. Sepulchre, R. (2000), "Slow peaking and low-gain designs for global stabilisation on nonlinear systems", IEEE T. Autom. Control, 45, 453-461. https://doi.org/10.1109/9.847724
  57. Sepulchre, R., Jankovic, M. and Kokotovic, P.V. (1997), "Constructive nonlinear control. Series in communications and control engineering", Springer, Berlin.
  58. Shen, W., Zhu, S., Zhu, H. and Xu, Y.L. (2016), "Electromagnetic energy harvesting from structural vibrations during earthquakes", Smart Struct. Syst., 18(3), 449-470. https://doi.org/10.12989/sss.2016.18.3.449
  59. Shi Y. and Fang H. (2010), "Kalman filter-based identification for systems with randomly missing measurements in a network environment", Int. J. Control, 83(3), 538-551. https://doi.org/10.1080/00207170903273987
  60. Simoes, M.G., Bose, B.K. and Spiegel, R.J. (1997), "Design and performance evaluation of a fuzzy-logic-based variable-speed wind generation system", IEEE T. Ind. Appl., 33, 956-965. https://doi.org/10.1109/28.605737
  61. Singer, J., Wang, Y.T. and Bau, H.H. (1991), "Experimental control of chaos", Phys. Rev. Lett., 66, 1123-1125. https://doi.org/10.1103/PhysRevLett.66.1123
  62. Sontag, E.D. (1988a), "Smooth stabilization implies coprime factorization", IEEE T. Automat. Contr., 34, 435-443.
  63. Sontag, E.D. (1989), "Remarks on stabilisation and input-to-state stability", Proceedings of the 28th IEEE Conference on Decision Control, Tampa, FL.
  64. Sontag, E.D. and Wang, Y. (1995), "On characterizations of the inputto-state stability property", Syst. Control Lett., 24, 351-359. https://doi.org/10.1016/0167-6911(94)00050-6
  65. Steinberg A. M., and I. Kadushin, "Stabilization of nonlinear systems with dither control," J. Math. Analysis and Application 43, 273-284 (1973). https://doi.org/10.1016/0022-247X(73)90275-8
  66. Su, P., Shang, C., Chen, T. and Shen, Q/ (2017), "Exploiting data reliability and fuzzy clustering for journal ranking," IEEE Trans. Fuzzy Syst., 25(5), 1306-1319. https://doi.org/10.1109/TFUZZ.2016.2612265
  67. Sun, Q., Li, R. and Zhang, P. (2003), "Stable and optimal adaptive fuzzy control of complex systems using fuzzy dynamic model", Fuzzy Set. Syst., 133, 1-17. https://doi.org/10.1016/S0165-0114(02)00124-0
  68. Takagi, T. and Sugeno, M. (1985), "Fuzzy identification of systems and its applications to modeling and control", IEEE T. Syst. Man Cy., 15, 116-132.
  69. Tanaka, K. and Sano, M. (1994), "A robust stabilization problem of fuzzy control systems and its application to backing up control of a truck-trailer", IEEE T. Fuzzy Syst., 2, 119-134.. https://doi.org/10.1109/91.277961
  70. Tanaka, K. and Sano, M. (1994), "On the concepts of regulator and observer of fuzzy control systems", Proceedings of the 3rd IEEE international Conference on Fuzzy Systems, Orlando, FL.
  71. Tanaka, K. and Wang, H.O. (1997), "Fuzzy regulators and fuzzy observers: a linear matrix inequality approach", Proceedings of the 36th American on Decision & Control.
  72. Tanaka, K., Ikeda, T. and Wang, H.O. (1996), "Robust stabilization of a class of uncertain nonlinear systems via fuzzy control: quadratic stability, $H{\infty}$ control theory, and linear matrix inequalities", IEEE T. Fuzzy Syst., 4, 1-13. https://doi.org/10.1109/91.481840
  73. Tanaka, K., Ikeda, T. and Wang, H.O. (1998), "Fuzzy regulators and fuzzy observers: relaxed stability conditions and LMI-based designs", IEEE T. Fuzzy Syst., 6, 250-265. https://doi.org/10.1109/91.669023
  74. Tsai, P.W., Kham, M.K., Pan, J.S. and Liao, B.Y. (2012), "Interactive artificial bee colony supported passive continuous authentication system", IEEE Syst. J., 1-11.
  75. Tsai, P.W., Pan, J.S., Liao, B.Y. and Chu, S.C. (2009), "Enhanced artificial bee colony optimization", Int. J. Innov. Comput. Inform. Control, 5(12), 5081-5092.
  76. Tsai, P.W., Pan, J.S., Liao, B.Y., Tsai, M.J. and Vaci, I. (2012a), "Bat algorithm inspired algorithm for solving numerical optimization problems", Appl. Mech. Mater., 148-149, 134-137.
  77. Tyan, C.Y., Wang, P.P. and Bahler, D.R. (1996), "An application on intelligent control using neural network and fuzzy logic", Neurocomputing, 12, 345-363. https://doi.org/10.1016/0925-2312(95)00072-0
  78. Wang, H.O. and Abed, E.H. (1995), "Bifurcation control of a chaotic system", Automatica, 31, 1213-1226. https://doi.org/10.1016/0005-1098(94)00146-A
  79. Wang, H.O. and Tanaka, K. (1996), "An LMI-based stable fuzzy control of nonlinear systems and its application to control of chaos", IEEE Int. Conf. on Fuzzy Syst., 1433-1438.
  80. Wang, H.O., Tanaka, K. and Griffin, M. (1996), "An approach to fuzzy control of nonlinear systems: stability and design issues", IEEE T. Fuzzy Syst., 4, 14-23. https://doi.org/10.1109/91.481841
  81. Wang, H.O., Tanaka, K. and Griffin, M.F. (1996), "An approach to fuzzy control of nonlinear systems: stability and design issues", IEEE T. Fuzzy Syst., 4, 14-23. https://doi.org/10.1109/91.481841
  82. Wang, Z.H., Chang, C.C. and Li, M.C. (2012), "Optimizing least-significant-bit substitution using cat swarm optimization strategy", Inform. Sciences, 192, 98-108. https://doi.org/10.1016/j.ins.2010.07.011
  83. Warga, J. (1962), "Relaxed variational problems", J. Math. Anal. Appl., 4, 111-128. https://doi.org/10.1016/0022-247X(62)90033-1
  84. Yan, B., Zhang, S., Zhang, X., Wang, C. and Wu, C. (2017), "Self-powered electromagnetic energy harvesting for the low power consumption electronics: Design and experiment", Int. J. Appl. Electromagn. Mech., 54, 1-11. https://doi.org/10.3233/JAE-160043
  85. Yen, G.G. (1996), "Health monitoring of vibration signatures in rotorcraft wings", Neural Process. Lett., 4, 127-137. https://doi.org/10.1007/BF00426021
  86. Yu, L. and Giurgiutiu, V. (2005), "Advanced signal processing for enhanced damage detection with piezoelectric wafer active sensors", Smart Struct. Syst., 1(2), 185-215. https://doi.org/10.12989/sss.2005.1.2.185
  87. Zhu, Y., Zhang, Q., Wei, Z. and Zhang, L. (2013), "Robust stability analysis of Markov jump standard genetic regulatory networks with mixed time delays and uncertainties", Neurocomputing, 110(13), 44-50. https://doi.org/10.1016/j.neucom.2012.09.033