Dynamic Matrix Control and Tuning Parameters Analysis for a DC Motor System Control
DOI:
https://doi.org/10.48084/etasr.2300Keywords:
model predictive control (MPC), dynamic matrix control (DMC), tuning parameters, DC motor controlAbstract
Model predictive control (MPC) in system control industry overrides the challenges of conventional controllers in controlling complex systems. However, for efficient control, it is essential to find the best combination of parameter values. In this paper, we present the implementation of a multivariable dynamic matrix control (DMC) algorithm. An industrial system consisting of a DC motor, coupled to a mechanical load, the assembly associated with an electronic speed variator was considered to test the implemented DMC controller. DMC’s tuning parameter analysis on the manipulated inputs and their variations on the controlled outputs was performed. Results guarantee that efficient control was presented.
References
A. T. Boum, “Observer based and quadratic dynamic matrix control of a fluid catalytic cracking unit: A comparison study”, International Journal of Computer Applications, Vol. 80, No. 3, pp. 1-8, 2013
J. M. Lopez-Guede, B. Fernandez-Gauna, M. Grana, F. Oterino, “On the Influence of the Prediction Horizon in Dynamic Matrix Control”, International Journal of Control, Vol. 3, No. 1, pp. 22-30, 2013
E. F. Camacho, C. Bordons, Model Predictive Control in the Process Industry, Springer Science & Business Media, 2012
S. Joe Qin, T. A. Badgwell, “A survey of industrial model predictive control technology”, Control Engineering Practice, Vol. 11, No. 7, pp. 733-764, 2003
J. Richalet, A. Rault, J. Testud, J. Papon, “Model predictive heuristic control: Applications to industrial processes”, Automatica, Vol. 14, No. 5, pp. 413-428, 1978
N. Vatsa, Tuning Parameters of Dynamic Matrix Control, PhD Thesis, National Institute of Technology Rourkela, India, 2011
G. M. de Almeida, M. A. de S. L. Cuadro, R. P. P. Amarai, J. L. F. Salles, “Optimal tuning parameters of the dynamic matrix predictive controller with ant colony optimization”, 11th IEEE/IAS International Conference on Industry Applications, Juiz de Fora, Brazil, December 7-10, 2014
P. Bagheri, A. K. Sedigh, “Robust tuning of dynamic matrix controllers for first order plus dead time models”, Applied Mathematical Modelling, Vol. 39, No. 22, pp. 7017-7031, 2015
A. S. Yamashita, A. C. Zanin, D. Odloak, “Tuning of model predictive control with multi-objective optimization”, Brazilian Journal of Chemical Engineering, Vol. 33, No. 2, pp. 333-346, 2016
D. Dougherty, D. J. Cooper, “Tuning guidelines of a dynamic matrix controller for integrating (non-self-regulating) processes”, Industrial & Engineering Chemistry Research, Vol. 42, No. 8, pp. 7039-7052, 2003
C. M. Reverter, J. Ibarrola, J. M. Cano-Izquierdo, “Tuning rules for a quick start up in Dynamic Matrix Control”, ISA Transactions, Vol. 53, No. 2, pp. 612-627, 2014
P. Acharya, Performance Analysis of Model Predictive Control For Distillation Column, PhD Thesis, National Institute of Technology Rourkela, India, 2016
R. E. Kalman, “Contributions to the theory of optimal control”, Boletin de la Sociedad Matematica Mexicana, Vol. 5, No. 2, pp. 102-119, 1960
C. R. Cutler, B. L. Ramaker, “Dynamic matrix control-a computer control algorithm”, The National Meeting of the American Institute of Chemical Engineers, Houston, USA, April 1979
N. R. Ruchika, “Model predictive control: History and development”, International Journal of Engineering Trends and Technology, Vol. 4, No. 6, pp. 2600-2602, 2013
R. Shridhar, D. J. Cooper, “A novel tuning strategy for multivariable model predictive control”, ISA Transactions, Vol. 36, No. 4, pp. 273-280, 1998
C. R. Cutler, Dynamic Matrix Control, An Optimal Multivariable Control Algorithm with Constraints, PhD Thesis, University of Houston, USA, 1983
L. Bitjoka, M. Ndje, A. T. Boum, J. Song-Manguelle, “Implementation of quadratic dynamic matrix control on arduino due ARM cortex-M3 microcontroller board”, Journal of Engineering Technology, Vol. 6, No. 2, pp. 682-695, 2017
A. A. Kheriji, F. Bouani, M. Ksouri, M. B. Ahmed, “A microcontroller implementation of model predictive control”, International Journal of Electrical and Information Engineering, Vol. 5, No. 5, pp. 600-606, 2011
A. K. Abbes, F. Bouani, M. Ksouri, “A microcontroller implementation of constrained model predictive control”, International Journal of Computer, Electrical, Automation, Control and Information Engineering, Vol. 5, No. 8, pp. 878-885, 2011
C. Ekaputri, A. Syaichu-Rohman, “Model predictive control (MPC) design and implementation using algorithm-3 on board SPARTAN 6 FPGA SP605 evaluation kit”, IEEE 3rd International Conference on Instrumentation Control and Automation, Ungasan, Indonesia, August 28-30, 2013
L. Malouche, A. K. Abbes, F. Bouani, “Automatic model predictive control implementation in a high-performance microcontroller”, IEEE 12th International Multi-Conference on Systems, Signals & Devices, Mahdia, Tunisia, March 16-19, 2015
R. Nagarajan, S. Sathishkumar, S. Deepika, G. Keerthana, J. K. Kiruthika, R. Nandhini, “Implementation of Chopper Fed Speed Control of Separately Excited DC Motor Using PI Controller”, International Journal of Engineering and Computer Science, Vol. 6, No. 3, pp. 20631-20633, 2017
V. H. Haji, C. A. Monje, “Fractional-order PID control of a chopper-fed DC motor drive using a novel firefly algorithm with dynamic control mechanism”, Soft Computing, Vol. 22, No. 18, pp. 6135-6146, 2018
S. Li, K. Y. Lim, D. G. Fisher, “A state space formulation for model predictive control”, AIChE Journal, Vol. 35, No. 2, pp. 241-249, 1989
E. F. Camacho, C. Bordons, Model Predictive Control, Springer-Verlag, 1998
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