Abstract
The aim of this paper is to describe software implementation of the Dynamic Matrix Control (DMC) algorithm using a microcontroller with fixed-point arithmetic. A 32-bit RISC ARM platform is used, which is cheap, but quite a powerful hardware system. To prevent register overflow and drastic loss of precision, a partial shifting of values technique is performed. The DMC algorithm with fixed-point arithmetic is applied to a laboratory thermal process and the obtained results are compared with those of the DMC algorithm implemented in floating-point arithmetic.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bamimore, A., Taiwo, O., King, R.: Comparison of two nonlinear model predictive control methods and implementation on a laboratory three tank system. In: Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference, pp. 5242–5247 (2011)
Jerez, J.L., Constantinides, G.A., Kerrigan, E.C.: Towards a fixed point QP solver for predictive control. In: Proceedings of the 51st IEEE Annual Conference on Decision and Control, pp. 675–680 (2012)
Kayacan, E., Ramon, H., Saeys, W.: Learning in centralized nonlinear model predictive control: application to an autonomous tractor-trailer system. IEEE Trans. Control Syst. Technol. 23(1), 197–205 (2015)
Lin, C.-Y., Liu, Y.-C.: Precision tracking control and constraint handling of mechatronic servo systems using model predictive control. IEEE/ASME Trans. Mechatron. 17(4), 593–605 (2012)
Longo, S., Kerrigan, E.C., Constantinides, G.A.: A predictive control solver for low-precision data representation. In: Proceedings of the European Control Conference, pp. 3590–3595 (2013)
Ławryńczuk, M.: Computationally Efficient Model Predictive Control Algorithms: A Neural Network Approach. Stud. Syst. Decis. Control 3 (2014). Springer, Heidelberg
Patrinos, P., Guiggiani, A., Bemporad, A.: Fixed-point dual gradient projection for embedded model predictive control. In: Proceedings of the European Control Conference, pp. 3602–3607 (2013)
Shi, J., Jiang, Q., Cao, Z., Zhou, H., Yang, Y.: Design method of PID-type model predictive iterative learning control based on the two-dimensional generalized predictive control scheme. In: Proceedings of the 12th International Conference on Control Automation Robotics and Vision, pp. 452–457 (2012)
Tatjewski, P.: Advanced Control of Industrial Processes: Structures and Algorithms. Springer, London (2007)
Tousain, R.L., Bosgra, O.H.: Efficient dynamic optimization for nonlinear model predictive control-application to a high-density poly-ethylene grade change problem. In: Proceedings of the 39th IEEE Conference on Decision and Control, vol. 1, pp. 760–765 (2000)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Chaber, P. (2016). Implementation of Dynamic Matrix Control Algorithm Using a Microcontroller with Fixed-Point Arithmetic. In: Szewczyk, R., Zieliński, C., Kaliczyńska, M. (eds) Challenges in Automation, Robotics and Measurement Techniques. ICA 2016. Advances in Intelligent Systems and Computing, vol 440. Springer, Cham. https://doi.org/10.1007/978-3-319-29357-8_5
Download citation
DOI: https://doi.org/10.1007/978-3-319-29357-8_5
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-29356-1
Online ISBN: 978-3-319-29357-8
eBook Packages: EngineeringEngineering (R0)