Page 208 - 2024-Vol20-Issue2
P. 208

204 |                                                                                  Al-mtory, Alnahwi & Ali

                                                                  TABLE VIII.
THE TRANSIENT PARAMETER WHEN WITHOUT PID CONTROLLER AND WITH PID CONTROLLER AFTER OPTIMIZED

               THE PROPORTIONAL COEFFICIENT, INTEGRAL COEFFICIENT, AND DERIVATIVE COEFFICIENT

#System    System-A            System-B                         System-C     System-D                System-E

    tr   without PID with PID  without PID with PID  without PID with PID    without PID with PID  without PID with PID
    ts
   MP    0.3505   0.0099       0.1877   0.0129       2.1694     0.2339       7.3892   1.5683       0.8843      0.403

         15.1287  0.0175       24.5412  0.0229       33.5405    0.7756       14.1136  2.7102       1.5894      0.628

         77.9429     0.005     377.305   0           7.1052               0  0 1.80E-04              00

Variables                                                    TABLE IX.                                     CDOA
    X1            Compassion between the result of different algorithms for cantilever beam problem        6.0265
    X2                                                                                                     4.8966
    X3             PSO GA WWO MVO SCA WOA                                                                  4.5686
    X4            6.05099 6.03277 5.99823 6.05099 5.67787 5.78636                                          3.5013
    X5            4.93196 5.31962 5.24612 4.93196 5.33850 5.57995                                          2.0950
   F(x)           5.2118 4.48431 4.49356 5.21118 4.86170 4.28758                                           1.31251
                  3.94183 3.48147 3.60865 3.94183 3.45494 3.74891
                  1.88577 2.15591 2.13733 1.88577 2.30102 2.16705
                  1.37063 1.33655 1.33702 1.37063 1.34650 1.34251

                    REFERENCES                                   [7] M. Azizi, S. Talatahari, N. Khodadadi, and P. Sareh,
                                                                      “Multiobjective atomic orbital search (moaos) for global
[1] I. Fister Jr, X.-S. Yang, I. Fister, J. Brest, and D. Fis-        and engineering design optimization,” IEEE Access,
     ter, “A brief review of nature-inspired algorithms for           vol. 10, pp. 67727–67746, 2022.
     optimization,” arXiv preprint arXiv:1307.4186, 2013.
                                                                 [8] Z. Zandi, E. Afjei, and M. Sedighizadeh, “Reactive
[2] C. Blum, “Ant colony optimization: Introduction and               power dispatch using big bang-big crunch optimization
     recent trends,” Physics of Life reviews, vol. 2, no. 4,          algorithm for voltage stability enhancement,” in 2012
     pp. 353–373, 2005.                                               IEEE International Conference on Power and Energy
                                                                      (PECon), pp. 239–244, IEEE, 2012.
[3] X.-S. Yang, “Firefly algorithm, stochastic test functions
     and design optimisation,” International journal of bio-     [9] R. Formato, “Central force optimization: a new meta-
     inspired computation, vol. 2, no. 2, pp. 78–84, 2010.            heuristic with applications in applied electromagnetics,”
                                                                      Progress in electromagnetics research, vol. 77, pp. 425–
[4] J. Kennedy and R. Eberhart, “Particle swarm optimiza-             491, 2007.
     tion,” in Proceedings of ICNN’95-international confer-
     ence on neural networks, vol. 4, pp. 1942–1948, ieee,      [10] G. Zhao, X. Wang, H. Zhao, and Z. Jiang, “An im-
    1995.                                                             proved pedestrian dead reckoning algorithm based on
                                                                      smartphone built-in mems sensors,” AEU-International
[5] X.-S. Yang and S. Deb, “Engineering optimisation by               Journal of Electronics and Communications, vol. 168,
     cuckoo search,” International Journal of Mathematical            p. 154674, 2023.
    Modelling and Numerical Optimisation, vol. 1, no. 4,
     pp. 330–343, 2010.                                         [11] R. S. Ali, F. M. Alnahwi, and A. S. Abdullah, “A modi-
                                                                      fied camel travelling behaviour algorithm for engineer-
[6] C. Zhao and Y. Zhou, “A complex encoding flower polli-            ing applications,” Australian Journal of Electrical and
     nation algorithm for global numerical optimization,” in          Electronics Engineering, vol. 16, no. 3, pp. 176–186,
    Intelligent Computing Theories and Application: 12th              2019.
    International Conference, ICIC 2016, Lanzhou, China,
    August 2-5, 2016, Proceedings, Part I 12, pp. 667–678,      [12] T.-C. Chen, P.-W. Tsai, S.-C. Chu, and J.-S. Pan, “A
     Springer, 2016.                                                  novel optimization approach: bacterial-ga foraging,” in
   203   204   205   206   207   208   209   210   211   212   213