Determining configuration parameters for proportionally integrated differentiating controllers by arranging the poles of the transfer function on the complex plane
DOI:
https://doi.org/10.15587/1729-4061.2021.242869Keywords:
automatic control, PID controller, system of equations, configuration parameters, process quality indicatorsAbstract
This paper reports a solution to the problem of determining the configuration parameters of PID controllers when arranging the poles of the transfer function of a linear single-circuit automated control system for a predefined set of control objects.
Unlike known methods in which the task to find the optimal settings of a PID controller is formed as a problem of nonlinear programming, in this work a similar problem is reduced to solving a system of linear algebraic equations.
The method devised is based on the generalized Viète theorem, which establishes the relationship between the parameters and roots of the characteristic equation of the automatic control system. It is shown that for control objects with transfer functions of the first and second orders, the problem of determining the configuration parameters of PID controllers has an unambiguous solution. For control objects with transfer functions of the third and higher orders, the generated problem is reduced to solving the redefined system of linear algebraic equations that has an unambiguous solution when the Rouché–Capelli theorem condition is met.
Such a condition can be met by arranging one of the roots of the characteristic equation of the system on a complex plane. At the same time, the requirements for the qualitative indicators of the system would not always be met. Therefore, alternative techniques have been proposed for determining the configuration parameters of PID controllers. The first of these defines configuration parameters as a pseudo solution to the redefined system of linear algebraic equations while the second produces a solution for which the value of the maximum residual for the system of equations is minimal.
For each case, which was used to determine the settings of PID controllers, such indicators of the control process as overshooting and control time have been determined
References
- Denisenko, V. (2007). PID-reguliatory: voprosy realizatsii. Ch. 1. Sovremennye tekhnologii avtomatizatsii, 1, 78–88.
- Ziegler, J. G., Nichols, N. B., Rochester, N. Y. (1942). Optimum Settings for Automatic Controller. Transactions of the A.S.M.E, 759–765.
- Li, K. (2013). PID Tuning for Optimal Closed-Loop Performance With Specified Gain and Phase Margins. IEEE Transactions on Control Systems Technology, 21 (3), 1024–1030. doi: http://doi.org/10.1109/tcst.2012.2198479
- Padhan, D. G., Majhi, S. (2013). Enhanced cascade control for a class of integrating processes with time delay. ISA Transactions, 52 (1), 45–55. doi: http://doi.org/10.1016/j.isatra.2012.08.004
- Rotach, V. Ia. (2008). Teoriia avtomaticheskogo upravleniia. Moscow: Izdatelskii dom MEI, 400.
- Das, D. C., Roy, A. K., Sinha, N. (2012). GA based frequency controller for solar thermal-diesel-wind hybrid energy generation/energy storage system. International Journal of Electrical Power & Energy Systems, 43 (1), 262–279. doi: http://doi.org/10.1016/j.ijepes.2012.05.025
- Zhang, D., Li, H. (2008). A Stochastic-Based FPGA Controller for an Induction Motor Drive With Integrated Neural Network Algorithms. IEEE Transactions on Industrial Electronics, 55 (2), 551–561. doi: http://doi.org/10.1109/tie.2007.911946
- Gorripotu, T. S., Kumar, D. V., Boddepalli, M. K., Pilla, R. (2018). Design and analysis of BFOA optimised PID controller with derivative filter for frequency regulation in distributed generation system. International Journal of Automation and Control, 12 (2), 291–323. doi: http://doi.org/10.1504/ijaac.2018.090808
- Das, S., Biswas, A., Dasgupta, S., Abraham, A. (2009). Bacterial Foraging Optimization Algorithm: Theoretical Foundations, Analysis, and Applications. Foundations of Computational Intelligence. Vol. 3. Berlin, Heidelberg: Springer, 23–55. doi: http://doi.org/10.1007/978-3-642-01085-9_2
- Dudnikov, V. G., Kazakov, A. V., Sofieva, Iu. et. al. (1987). Avtomaticheskoe upravlenie v khimicheskoi promyshlennosti. Moscow: Khimiia, 368.
- Taoussi, M., Karim, M., Bossoufi, B., Hammoumi, D., Lagrioui, A., Derouich, A. (2016). Speed variable adaptive backstepping control of the doubly-fed induction machine drive. International Journal of Automation and Control, 10 (1), 12–33. doi: http://doi.org/10.1504/ijaac.2016.075140
- Horbiichuk, M. I., Povarchuk, D. D. (2017). Metod nalashtuvannia parametriv PI- i PID-rehuliatoriv systemy avtomatychnoho keruvannia protsesom dvostupenevoi separatsii nafty. Naukovyi visnyk IFNTUNH, 2 (43), 89–55.
- Vinberg, E. B. (2014). Kurs algebry. Moscow: I-vo MTSNMO, 590.
- Dorf, R., Bishop, R. (2002). Sovremennye sistemy upravleniia. Moscow: Laboratoriia bazovykh znanii, 832.
- Voevodin, V. V. (1977). Vychislitelnye osnovy lineinoi algebry. Moscow: Nauka, 304.
- Ilin, V. A., Kim, G. D. (2007). Lineinaia algebra i analiticheskaia geometriia. Moscow: TK Velbi, Izd-vo Prospekt, 400.
- Paige, C. C., Saunders, M. A. (1982). LSQR: An Algorithm for Sparse Linear Equations and Sparse Least Squares. ACM Transactions on Mathematical Software, 8 (1), 43–71. doi: http://doi.org/10.1145/355984.355989
- Barkalova, O. S. (2012). Korrektsiia nesobstvennykh zadach lineinogo programmirovaniia v kanonicheskoi forme po minimaksnomu kriteriiu. Zhurnal vychislitelnoi matematiki i matematicheskoi fiziki, 52 (12), 2178–2189.
- Raskin, L. G., Seraia, O. V., Ivanchikhin, Iu. V. (2012). Information analysis incompatible systems of linear equations. Minimax solutions. Eastern-European Journal of Enterprise Technologies, 5 (4 (59)), 40–44. Available at: http://journals.uran.ua/eejet/article/view/4527
- Faddeev, A. K., Faddeeva, V. N. (2021). Vychislitelnye metody lineinoi algebry. Saint Petersburg: Lan, 736.
- Diakonov, V. P. (2012). MATLAB. Polnii samouchitel. Moscow: DMK Press, 768.
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