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Optimal tuning procedure for FOPID controller of integrated industrial processes with deadtime

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Industrial processes such as batch distillation columns, supply chain, level control etc. integrate dead times in the wake of the transportation times associated with energy, mass and information. The dead time, the cause for the rise in loop variability, also results from the process time and accumulation of time lags. These delays make the system control poor in its asymptotic stability, i.e. its lack of self-regulating savvy. The haste of the controller’s reaction to disturbances and congruence with the design specifications are largely influenced by the dead time; hence it exhorts a heed. This article is aimed at answering the following question: “How can a fractional order proportional integral derivative controller (FOPIDC) be tuned to become a perfect dead time compensator apposite to the dead time integrated industrial process?” The traditional feedback controllers and their tuning methods do not offer adequate resiliency for the controller to combat out the dead time. The whale optimization algorithm (WOA), which is a nascent (2016 developed) swarm-based meta-heuristic algorithm impersonating the hunting maneuver of a humpback whale, is employed in this paper for tuning the FOPIDC. A comprehensive study is performed and the design is corroborated in the MATLAB/Simulink platform using the FOMCON toolbox. The triumph of the WOA tuning is demonstrated through the critical result comparison of WOA tuning with Bat and particle swarm optimization (PSO) algorithm-based tuning methods. Bode plot based stability analysis and the time domain specification based transient analysis are the main study methodologies used.
Rocznik
Strony
art. no. e139954
Opis fizyczny
Bibliogr. 25 poz., rys., tab.
Twórcy
autor
  • Arunachala College of Engineering For Women, India
  • Arunachala College of Engineering For Women, India
  • St. Xavier’s Catholic College of Engineering, India
Bibliografia
  • [1] A. Tepljakov, “Fractional-order Modeling and Control of Dynamic Systems”, Ph.D. Thesis, Dept. Comput. Syst., Tallinn University of Technology, Tallinn, Estonia, 2017.
  • [2] J.C. Shen, “New tuning method for PID controller”, ISA Trans., vol. 41, no. 4, pp. 473–484, 2002, doi: 10.1016/S0019-0578(07)60103-7.
  • [3] G.M. Malwatkara, S.H. Sonawane, and L.M. Waghmare, “Tuning PID Controllers for higher order oscillatory systems with improved performance”, ISA Trans., vol. 48, pp. 347–353, 2009, doi: 10.1016/S0019-0578(07)60103-7.
  • [4] R. Rajesh, “Optimal tuning of FOPID controller based on PSO algorithm with reference model for a single conical tank system”, SN Appl. Sci., vol. 1, p. 758, 2019, doi: 10.1007/s42452-019-0754-3.
  • [5] A. Tepljakov, E. Petlenkov, J. Belikov, and E.A. Gonzalez, “Design of retuning fractional PID controllers for a closed loop magnetic levitation control system”, Proc. 13th Int. Conf. Control, Automation, Robotics and Vis., 2014, pp. 1345–1350, doi: 10.1109/ICARCV.2014.7064511.
  • [6] M. Zhang and G. Wang, “Study on integrating process with dead time”, Proc. 29th Chinese Control Conf., 2010, pp. 207–209.
  • [7] F. Peterle, M. Rampazzo, and A. Beghi, “Control of second order processes with dead time: the predictive PID solutions”, IFAC Papers Online, vol. 51, no. 4, pp. 793–798, 2018, doi: 10.1016/j.ifacol.2018.06.183.
  • [8] I. Podlubny, “Fractional-order systems and PIλ Dμ -controllers”, IEEE Trans. Autom. Control, vol. 44, no. 1, pp. 208–214, Jan 1999, doi: 10.1109/9.739144.
  • [9] I. Podlubny, L. Dorcák, and I. Kostial, “On fractional derivatives, fractional-order dynamic systems and PIλ Dμ -controllers”, Proc. 36th IEEE Conf. on Decision and Control, 1997, vol. 5, pp. 4985–4990.
  • [10] Z. Bingul and O .Karahan, “Comparison of PID and FOPID controllers tuned by PSO and ABC algorithms for unstable and integrating systems with time delay”, Optim. Control Appl. Methods, vol. 39, no. 5, pp. 1581–1596, 2018, doi: 10.1002/oca.249.
  • [11] M. Cech and M .Schlegel, “The fractional-order PID controller outperforms the classical one”, Conf. Process Control, pp. 1–6, 2006.
  • [12] C.A. Monje, Y.Q. Chen, B.M. Vinagre, D. Xue, and V. Feliu, “Fractional-Order Systems and Controls: Fundamentals and Applications”, in Advances in Industrial Control, 2010, doi: 10.1007/978-1-84996-335-0.
  • [13] D. Valerio and J. Costa, “A review of tuning methods for fractional PIDs”, in Preprint 4th IFAC Workshop on Fractional Differentiation and its Applications, 2010.
  • [14] M. Buslowicz, “Stability conditions for linear continuous time fractional order state delayed systems”, Bull. Pol. Acad. Sci. Tech. Sci., vol. 64, no. 1, pp. 3–7, 2016, doi: 10.1515/bpasts-2016-0001.
  • [15] C. Ionesai and D. Copot, “Hands on MPC tuning for industrial application”, Bull. Pol. Acad. Sci. Tech. Sci., vol 67, no. 5, pp. 925–945, 2019, doi: 10.24425/bpasts-2019-130877.
  • [16] D. Mozyrska, P. Ostalczyk and M. Wyrwas, “Stability conditions for fractional-order linear equations with delays”, Bull. Pol. Acad. Sci. Tech. Sci., vol. 66, no. 4, pp. 449–454, 2018, doi: 10.24425/124261.
  • [17] W. Jakowluk, “Optimal input signal design for fractional-order system identification”, Bull. Pol. Acad. Sci. Tech. Sci., vol. 67, no. 1, pp. 37- 44, 2019, doi: 10.24425/bpasts-.2019-127336.
  • [18] J. Klamka, J. Wyrwal and R. Zawiski, “On controllability of second order dynamical system survey”, Bull. Pol. Acad. Sci. Tech. Sci., vol. 65, no. 3, pp. 279–295, 2017, doi: 10.1515/bpast-2017-00320.
  • [19] S. Das, S. Saha, S. Das, and A. Gupta, “On the selection of tuning methodology of FOPID controllers for the control of higher order processes”, ISA Trans., vol. 50, no. 3, pp. 376–388, 2011, doi: 10.1016/j.isatra. 2011.02.003.
  • [20] H. Gozde and M.C. Taplamacioglu, “Comparative performance analysis of artificial bee colony algorithm for automatic voltage regulator (AVR) system”, J. Franklin Inst., vol. 348, no. 8, pp. 1927–1946, 2011, doi: 10.1016/j.jfranklin.2011.05.012.
  • [21] D.L. Zhang, Y.G. Tang, and X.P. Guan, “Optimum design of fractional order PID controller for an AVR system using an improved artificial bee colony algorithm”, Acta Auto. Sin., vol. 40, no. 5, pp. 973–979, 2014, doi: 10.1016/S1874-1029(5)60010-0.
  • [22] S. Das, I. Pan, S. Das, and A. Gupta, “A novel fractional order fuzzy PID controller and its optimal time domain tuning based on integral performance indices”, Eng. Appl. Artif. Intel., vol. 25, no. 2, pp. 430–442, Mar. 2012, doi: 10.1016/j.engappai.2011.10.004.
  • [23] L. Liu, “Optimization design on fractional order PID controller based on adaptive particle swarm Optimization algorithm”, Nonlinear Dyn., vol. 84, pp. 379–386, 2016, doi: 10.1007/s11071-015-2553-8.
  • [24] M. Seyedali and L. Andrew, “The whale optimization algorithm”, Adv. Eng. Soft., vol. 95, pp. 51–67, 2016, doi: 10.1016/j.advengsoft.2016.01.008.
  • [25] R.S. Preeti, H. Prakash Kumar, and P. Sidhartha, “Power system stability enhancement by fractional order multi input SSSC based controller employing whale optimization algorithm”, J. Electr. Syst. Inf. Technol., vol. 5, no. 3, pp. 326–2018, doi: 10.1016/j.jesit.2018.02.008.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-78671bfc-10be-4ccd-8a09-5a44ae9e65a6
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