PID CONTROLLER DESIGN FOR DECENTRALIZED TITO PROCESS USING MODIFIED DIFFERENTIAL EVOLUTION ALGORITHM

Jailsingh Bhookya and Ravi Kumar Jatoth

References

  1. [1] M.J. Lengare, R.H. Chile, and L.M. Waghmare, Design of decentralized controllers for MIMO processes, Computers & Electrical Engineering, 38(1), 2012, 140–147.
  2. [2] V.D. Hajare and B.M. Patre, Decentralized PID controller for TITO systems using characteristic ratio assignment with an experimental application, ISA Transactions, 59, 2015, 385–397.
  3. [3] W.-D. Chang and C.-Y. Chen, PID controller design for MIMO processes using improved particle swarm optimization, Circuits, Systems, and Signal Processing, 33(5), 2014, 1473–1490.
  4. [4] P.K. Paul, C. Dey and R.K. Mudi, Design of multi-loop IMC-PID controller for TITO process with dead time, 2016 2nd Int. Conf. on Control, Instrumentation, Energy & Communication (CIEC), Kolkata, 2016, 45–49.
  5. [5] D.K. Maghadea and B.M. Patre, Decentralized PI/PID controllers based on gain and phase margin specifications for TITO processes, ISA Transactions, 51, 2012, 550–558.
  6. [6] C. Rajapandiyan and M. Chidambaram, Closed-loop identification of multivariable systems by optimization method, Industrial & Engineering Chemistry Research, 51(3), 2012, 1324–1336.
  7. [7] Q. Xiong, W.-J. Cai, and M.-J. He, Equivalent transfer function method for PI/PID controller design of MIMO processes, Journal of Process Control, 17, 2007, 665–673.
  8. [8] Q.-G. Wang, T.-H. Lee, and Y. Zhang, Multiloop version of the modified Ziegler-Nichols method for two input two output processes, Industrial & Engineering Chemistry Research, 37, 1998, 4725–4733.
  9. [9] V. D. Hajare, B.M. Patre, A.A. Khandekar, and G.M. Malwatkar, Decentralized PID controller design for TITO processes with experimental validation, International Journal of Dynamics and Control, 2017, 583–595.
  10. [10] Y. Shen, Y. Sun, and S. Li, Adjoint transfer matrix based decoupling control for multivariable processes, Industrial & Engineering Chemistry Research, 51(50), 2012, 16419–16426.
  11. [11] P. Nordfeldt and T. Hagglund, Decoupler and PID controller design of TITO systems, Journal of Process Control, 16, 2006, 923–936.
  12. [12] C.S. Besta and M. Chidambaram, Tuning of multivariable PI controllers by BLT method for TITO systems, Chemical Engineering Communications, 203, 2016, 527–538.
  13. [13] K.J. Astrom and T.Hagglund, The future of PID control, Control Engineering Practice, 9, 2001, 1163–1175.
  14. [14] C. Rajapandiyan and M. Chidambaram, Controller design for MIMO processes based on simple decoupled equivalent transfer functions and simplified decoupler, Industrial & Engineering Chemistry Research, 51, 2012, 12398-12410.
  15. [15] Q. Xiong and W.-J. Cai, Effective transfer function method for decentralized control system design of multi-input multi-output processes, Journal of Process Control, 16, 2006, 773–784.
  16. [16] S. Tavakoli, I. Griffin, and P.J. Fleming, Tuning of decentralised PI (PID) controllers for TITO processes, Control Engineering Practice, 14, 2006, 1069–1080.
  17. [17] N. Chaudhary, R. Raj, K. Kiran, S. Nema, and P.K. Padhy, Design of multivariable PID controller using DE-PSO, International Journal Automation and Control, 9(3), 2015.
  18. [18] Y. Cheng and S. Li, A new pairing method for multivariable processes, Industrial & Engineering Chemistry Research, 49, 2010, 6115–6124.
  19. [19] S. Das, S.S. Mullick, and P.N. Suganthan, Recent advances in differential evolution – An updated survey, Swarm and Evolutionary Computation, 27, 2016, 1–30.
  20. [20] A. Moharam, M.A. El-Hosseini, and H.A. Ali, Design of optimal PID controller using hybrid differential evolutionand particle swarm optimization with an aging leader and challengers, Applied Soft Computing, 38, 2016, 727–737.
  21. [21] S. Das and P.N. Suganthan, Differential evolution: a survey of the state-of-the-art, IEEE Transactions on Evolutionary Computation, 15(1), 2011, 4–31.
  22. [22] M. Ali, M. Pant, and A. Abraham, A modified differential evolution algorithm and its application to engineering problems, 2009 Int. Conf. of Soft Computing and Pattern Recognition, Malacca, 2009, 196–201.
  23. [23] M. Sedraoui, Application of the multivariable predictive control on a distillation column using the optimization methods, Control and Intelligent Systems, 36(2), 2008, 111–118.
  24. [24] E.M. Boufounas and A. El Amrani, Optimal multivariable control for wind energy conversion systems using particle swarm optimization technique, Control and Intelligent Systems, 45(4),2017.
  25. [25] Q.B. Jin and Q. Liu, Decoupling proportional–integral–derivative controller design for multivariable processes with time delays, Industrial & Engineering Chemistry Research, 53, 2014, 765–777.

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