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Automatic Code Generation of MIMO Model Predictive Control Algorithms using Transcompiler

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Book cover Trends in Advanced Intelligent Control, Optimization and Automation (KKA 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 577))

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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.

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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.

    Google Scholar 

  • 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.

    Google Scholar 

  • 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.

    Google Scholar 

  • 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.

    Google Scholar 

  • 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.

    Google Scholar 

  • 6. R. Vilanova, V. M. Alfaro, and O. Arrieta, Robustness in PID Control, pp. 113–145. London: Springer London, 2012.

    Google Scholar 

  • 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.

    Google Scholar 

  • 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.

    Google Scholar 

  • 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.

    Google Scholar 

  • 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.

    Google Scholar 

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Correspondence to Patryk Chaber .

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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

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  • DOI: https://doi.org/10.1007/978-3-319-60699-6_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60698-9

  • Online ISBN: 978-3-319-60699-6

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