Hybrid optimization process applied to tuning of Dynamic Matrix Control: atudy case with DC motor

• Autorzy: Carvalho D. F. de , Ganzaroli C. A. , Couto L. do , Dias R. N. H. M. , Calixto W. P.

Identyfikatory

DOI

10.22149/teee.v2i2.98

• Konferencja: International Conference on Environment and Electrical Engineering (17 ; 06-09.06.2017 ; Milan, Italy)
• Języki publikacji: EN

Abstrakty

EN

This paper presents study about Dynamic Matrix Control (DMC) controller applied to speed control of DC motor. DMC controller parameters (prediction horizon, control horizon and damping rate of reference) are obtained through optimization methods employing heuristic, deterministic and hybrid strategies. The use of advanced control technique combined with using of optimization methods aims to achieve highly efficient control, reducing the transient state period and variations in steady state. These methods were applied on a simulation model in order to verify which one provides better control results.

Słowa kluczowe

EN

predictive control; deterministic optimization; heuristic optimization; hybrid optimization; DC motor

• Wydawca: EEEIC International Publishing
• Czasopismo: Transactions on Environment and Electrical Engineering
• Rocznik: 2017
• Tom: Vol. 2, No. 2
• Strony: 24--30
• Opis fizyczny: Bibliogr. 9 poz., rys., tab.

Twórcy

autor

Carvalho D. F. de

autor

Ganzaroli C. A.

autor

Couto L. do

autor

Dias R. N. H. M.

autor

Calixto W. P.

Bibliografia

• [1] W. Goncalves da Silva, “Speed control of electric drives in the presence of load disturbances,” Ph.D. dissertation, University of Newcastle upon Tyne, 1999.
• [2] N. Nise, Control Systems Engineering. John Wiley & Sons, 2007.
• [3] C.R. Cutler and B.L. Ramaker, “Dynamic matrix control?? A computer control algorithm,” in joint automatic control conference, no. 17, 1980, p. 72.
• [4] S.J. Qin and T.A. Badgwell, “A survey of industrial model predictive control technology,” Control engineering practice, vol. 11, no. 7, pp. 733-764, 2003.
• [5] E.F. Camacho and C. B. Alba, Model predictive control. Springer Science & Business Media, 2013.
• [6] W.P. Calixto, T.M. Pereira, J. Mota, A. Alves, E. Domingues, J. Domingos, A. Coimbra, and B. Alvarenga, “Development of mathematical operator to heuristic optimization algorithms applied to problem of geoprospection, In Portuguese,” TEMA (São Carlos), vol. 15, no. 2, pp. 177-194, 2014.
• [7] C.A. e. a. Ganzaroli, “Heuristic and deterministic strategies applied on a cascade pi controller tuning for speed control of a dc motor,” IEEE Control Systems Magazine, 2015.
• [8] S. Chapman, Electric machinery fundamentals. Tata McGraw-Hill Education, 2005.
• [9] Vasant, Pandian M., Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance, IGI Global, 2012.

Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).