A Microcontroller Implementation of Model Predictive Control

Authors: Amira Abbes Kheriji, Faouzi Bouani, Mekki Ksouri, Mohamed Ben Ahmed

Abstract:

Model Predictive Control (MPC) is increasingly being proposed for real time applications and embedded systems. However comparing to PID controller, the implementation of the MPC in miniaturized devices like Field Programmable Gate Arrays (FPGA) and microcontrollers has historically been very small scale due to its complexity in implementation and its computation time requirement. At the same time, such embedded technologies have become an enabler for future manufacturing enterprises as well as a transformer of organizations and markets. Recently, advances in microelectronics and software allow such technique to be implemented in embedded systems. In this work, we take advantage of these recent advances in this area in the deployment of one of the most studied and applied control technique in the industrial engineering. In fact in this paper, we propose an efficient framework for implementation of Generalized Predictive Control (GPC) in the performed STM32 microcontroller. The STM32 keil starter kit based on a JTAG interface and the STM32 board was used to implement the proposed GPC firmware. Besides the GPC, the PID anti windup algorithm was also implemented using Keil development tools designed for ARM processor-based microcontroller devices and working with C/Cµ langage. A performances comparison study was done between both firmwares. This performances study show good execution speed and low computational burden. These results encourage to develop simple predictive algorithms to be programmed in industrial standard hardware. The main features of the proposed framework are illustrated through two examples and compared with the anti windup PID controller.

Keywords: Embedded systems, Model Predictive Control, microcontroller, Keil tool.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1334217

References:

[1] T. Alamo, D. Ramirez, and E. Camacho, "Efficient implementation of constrained min-max model predictive control with bounded uncertainties: a vertex rejection approach," Journal of Process Control, vol. 15, pp. 149-158, 2005.
[2] E. Camacho and C. Bordons, Model Predictive Control. London: Springer, 2004.
[3] G. D. Nicolao, L. Magni, and R. Scattolini, "Robust predictive control of systems with uncertain impulse response," Automatica, vol. 32, no. 10, pp. 1475-1479, 1996.
[4] P. Campo and M. Morari, "Robust model predictive control," in Proceedings of American Control Conference, 1987, pp. 1021-1026.
[5] J. Rossiter, Model based predictive control: A practical approach. Robert H.Bishop, 2005.
[6] M. Kothare, V. Balakrishnan, and M. Morari, "Robust constrained model predictive control using linear matrix inequalities," Automatica, vol. 32, no. 10, pp. 1361-1379, 1996.
[7] Y. Wang and J. Rawlings, "A new robust model predictive control method 1: theory and computation," Journal of Process Control, vol. 14, pp. 231-247, 2002.
[8] G. Pannochia, "Robust model predictive control with guaranteed set point tracking," Journal of Process Control, vol. 14, pp. 927-937, 2004.
[9] B. Bouzouita, F. Bouani, and M. Ksouri, "Solving non convex minmax predictive controller," in Proceedings of Information, Decision and Control Conference, 2007.
[10] A. Kheriji, F. Bounani, and M. Ksouri, "Efficient implementation of constraind robust model predictive control using a state space model," in Proceedings of International Conference on Informatics in Control, Automation and Robotics (ICINCO), 2010.
[11] A. Kheriji, F. Bouani, and M. Ksouri, "Ggp approach to solve non convex min-max robust model predictive controller for a class constrained mimo systems," in Proceedings of the International Workshop on Symbolic and Numerical Methods, Modeling and applications to circuit design, (SM2ACD) CEDA competition, 2010.
[12] A. Kheriji, F. Bounani, and M. Ksouri, "A ggp approach to solve non convex min-max predictive controller for a class of constrained mimo systems described by state-space models," International Journal of Control Automations and Systems (IJCAS), vol. 9, no. 3, 2011, will appear in June.
[13] K. Ling, S. Yue, and J. Maciejowski, "A fpga implementation of model predictive control," in Proceedings of American Control Conference, 2006.
[14] U. R. Y. Jayaraman, "Fpga implementation of predictive control strategy for power factor correction," in Proceedings of World Academy of Science, Engineering and Technology, 2008.
[15] K. Ling, B. Wu, and J. Maciejowski, "Embedded model predictive control (mpc) using a fpga," in Proceedings of the 17th World Congress: The International Federation of Automatic Control, Seoul, Korea, 2008.
[16] K. Watanabet, K. Ikeda, T. Fukuda, and S. Tzafestas, "Adaptive generalized predictive control using a state space approach," in International Workshop on Intelligent Robots and Systems IROS, Osaka, Japan, 1991.
[17] G. Palomo, K. Hilton, and J. Rossiter, "Predictive control implementation in a plc using the iec 1131.3 programming standard," in Proceedings of American Control Conference, 2009.