GWO-BASED TUNING OF LQR–PID CONTROLLER FOR 3-DOF PARALLEL MANIPULATOR

Chandan Choubey and Jyoti Ohri

References

  1. [1] L. Ren, J.K. Mills, and D. Sun, Trajectory tracking control for a 3-DOF planar parallel manipulator using the convex synchronized control method, IEEE Transactions on Control Systems Technology, 16(4), 2008, 613–623.
  2. [2] Y.X. Su, B.Y. Duan, and C.H. Zheng, Nonlinear PID control of a six DOF parallel manipulator, IEEE Proceedings Control Theory Applications, 151(1), 2004, 95–102.
  3. [3] Y. Li and Y.Wang, Trajectory tracking control of a redundantly actuated parallel robot using diagonal recurrent neural network, Proceedings International Conf. Natural Computing, Tianjin, China, IEEE, 2009, 292–296.
  4. [4] A. Abougarair, Controllers comparison to balancing and trajectory tracking a two wheeled mobile robot, International Journal of Robotics and Automation (IJRA), 5(1), 2019, 28–31.
  5. [5] S. Das, I. Pan, K. Halder, S. Das, and A. Gupta, LQR based improved discrete PID controller design via optimum selection of weighting matrices using fractional order integral performance index, Applied Mathematical Modelling, 37(6),2013, 4253–4268.
  6. [6] S. Saha, S. Das, S. Das, and A. Gupta, A conformal mappingbased fractional order approach for sub-optimal tuning of PID controllers with guaranteed dominant pole placement, Communications in Nonlinear Science and Numerical Simulation,17(9), 2012, 3628–3642.
  7. [7] S.K Verma, S. Yadav, and S.K. Nagar, Optimization of fractional order PID controller using grey wolf optimizer, Journal of Control Automation and Electrical Systems, 28(3), 2017,314–322.
  8. [8] S.K. Oh, HJ. Jang, and W.A. Pedrycz, comparative experimental study of type-1/type-2 fuzzy cascade controller based on genetic algorithms and particle swarm optimization, Expert Systems with Applications, 38(9), 2011, 11217–11229.
  9. [9] L. Wang, C. Luo, M. Li, and J. Cai, Trajectory planning of an autonomous mobile robot by evolving ant colony system, International Journal of Robotics and Automation (IJRA),32(4), 2017, 406–413.
  10. [10] S. Li, W. Wu, and D. Ma, MPPT of photovoltaic system variable acceleration disturbance method based on genetic algorithm, International Journal of Robotics and Automation(IJRA), 33(2), 2018, 179–185.
  11. [11] L. Sheng and W. Li, Optimization design by genetic algorithm controller for trajectory control of a 3-RRR parallel robot, Algorithms Journal, 11(7), 2018, 2–13.
  12. [12] X. Shao, J. Zhang, and X. Zhang, Takagi-Sugeno fuzzy modelling and PSO-based robust LQR anti-swing control for overhead crane, Mathematical Problems in Engineering, 2019(21), 2019,1–14.
  13. [13] M.A. Sen and M. Kalyoncu, Grey wolf optimizer based tuning of a hybrid LQR-PID controller for foot trajectory control of a quadruped robot, Gazi University Journal of Science, 32(9),2019, 674–684.
  14. [14] N. Razmjooy, M. Ramezani, and A. Namadchian, A new LQR optimal control for a single-link flexible joint robot manipulator based on grey wolf optimizer, Majlesi Journal of Electrical Engineering, 10(3), 2016, 53–60.
  15. [15] L.W. Tsai and R. Stamper, A parallel manipulator with only translational degrees of freedom, Presented at the Proceedings of ASME, Design Engineering Technology Conference, Irvine, CA, 1997, 1–18.
  16. [16] H. Bolandi and S. Esmaeilzadeh, Exact tip trajectory tracking control of a flexible robot arm, International Journal of Robotics and Automation (IJRA), 26(1), 2011, 100–109.
  17. [17] L.W. Tsai, Robot analysis and design: the mechanics of serial and parallel manipulators (Hoboken, NY: John Wiley, 1999),134–142.
  18. [18] S. Mirjalili, S.M. Mirjalili, and A. Lewis, Grey wolf optimizer, Advances in Engineering Software, 69(7), 2014, 46–61.
  19. [19] S. Mirjalili, How effective is the grey wolf optimizer in training multi-layer perceptrons, Applied Intelligence, 43(1), 2015,150–161.
  20. [20] S. Shahrzad, S.Z. Mirjalili, and S.M. Mirjalili, Evolutionary population dynamics and grey wolf optimizer, Neural Computing and Applications, 26(5), 2014, 1257–1263.
  21. [21] C. Choubey and J. Ohri, Optimal trajectory generation fora 6-DOF parallel manipulator using grey wolf optimization algorithm, Robotica, 1(1), 2020, 1–17.
  22. [22] J. Kennedy, C. Sammut, and G.I. Webb, Particle swarm optimization, Encyclopedia of machine learning (Washington, DC: Springer, 2011), 760–766.
  23. [23] S. Panda and N.P. Padhy, Comparison of particle swarm optimization and genetic algorithm for FACTS-based controller design, International Journal of Applied Soft Computing, 8(4),2008, 1418–1427.
  24. [24] S. Ekinci, Application and comparative performance analysis of PSO and ABC algorithms for optimal design of multi-machine power system stabilizers, Gazi University Journal of Science,29(2), 2016, 323–334.
  25. [25] S.S. Rao, Engineering optimization, theory and practice, 4thed. (Hoboken, New Jersey: John Wiley, 2009).
  26. [26] T. Coleman, M.A. Branch, and A. Grace, MATLAB Global Optimization Toolbox User’s Guide, Massachusetts, USA, Available Online https://instruct.uwo.ca/engin sc/391b/downloads/optim_tb.pdf, accessed, 1990.

Important Links:

Go Back