Abstract
This paper describes a system for code auto-generation of Model Predictive Control algorithms for Multiple-Input, Multiple-Output processes. Transcompiler – the main part of the system – generates C code of the algorithm, basing on MATLAB code, which contains definition of both algorithms and its parameters. The resulting code is optimised for microcontrollers in terms of memory and computational power necessary for on-line calculation of the optimal values of manipulated variables. This approach may decrease the development time of prototype controllers and lower their cost. Tests are conducted using STM32 microcontroller for simulated processes and results are demonstrated and described.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
1. F. Salem and M. I. Mosaad, “A comparison between MPC and optimal PID controllers: Case studies,” in Michael Faraday IET International Summit 2015, pp. 59–65, 2015.
2. G. C. Goodwin et al., “Application of MPC incorporating Stochastic Programming to Type 1 diabetes treatment,” in 2016 American Control Conference (ACC), pp. 907–912, 2016.
3. X. Jiang et al., “Application based on fast online MPC in power inverter system,” in Proceedings of the 33rd Chinese Control Conference, pp. 7673–7678, 2014.
4. P. J. Serkies and K. Szabat, “Application of the MPC to the Position Control of the Two-Mass Drive System,” IEEE Transactions on Industrial Electronics, vol. 60, no. 9, pp. 3679–3688, 2013.
5. Y. Noda, T. Sumioka, and M. Yamakita, “An application of fast MPC for bike robot,” in 2012 Proceedings of SICE Annual Conference (SICE), pp. 540–545, 2012.
6. R. Vilanova, V. M. Alfaro, and O. Arrieta, Robustness in PID Control, pp. 113–145. London: Springer London, 2012.
7. M. Vukov et al., “Experimental validation of nonlinear MPC on an overhead crane using automatic code generation,” in 2012 American Control Conference (ACC), pp. 6264–6269, 2012.
8. P. Chaber and M. Ławryńczuk, “Effectiveness of PID and DMC control algorithms automatic code generation for microcontrollers: Application to a thermal process,” in 2016 3rd Conference on Control and Fault-Tolerant Systems (SysTol), pp. 618–623, 2016.
9. G. Takács et al., “Efficiency and performance of embedded model predictive control for active vibration attenuation,” in 2016 European Control Conference (ECC), pp. 1334–1340, 2016.
10. P. Chaber and M. Ławryńczuk, “Auto-generation of advanced control algorithms’ code for microcontrollers using transcompiler,” in Methods and Models in Automation and Robotics (MMAR), 2016 21st International Conference on, pp. 454–459, 2016.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Chaber, P., Ławryńczuk, M. (2017). Automatic Code Generation of MIMO Model Predictive Control Algorithms using Transcompiler. In: Mitkowski, W., Kacprzyk, J., Oprzędkiewicz, K., Skruch, P. (eds) Trends in Advanced Intelligent Control, Optimization and Automation. KKA 2017. Advances in Intelligent Systems and Computing, vol 577. Springer, Cham. https://doi.org/10.1007/978-3-319-60699-6_30
Download citation
DOI: https://doi.org/10.1007/978-3-319-60699-6_30
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-60698-9
Online ISBN: 978-3-319-60699-6
eBook Packages: EngineeringEngineering (R0)