Fast Analytical Model Predictive Controllers and Their Implementation for STM32 ARM Microcontroller
This paper describes fast versions of model predictive control (MPC) algorithms and their practical implementation using the STM32 ARM microcontroller. Two MPC algorithms are considered: Dynamic Matrix Control (DMC) and Generalized Predictive Control (GPC). Computationally efficient Fast DMC (FDMC)...
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| Veröffentlicht in: | IEEE transactions on industrial informatics Jg. 15; H. 8; S. 4580 - 4590 |
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| Sprache: | Englisch |
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IEEE
01.08.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| Abstract | This paper describes fast versions of model predictive control (MPC) algorithms and their practical implementation using the STM32 ARM microcontroller. Two MPC algorithms are considered: Dynamic Matrix Control (DMC) and Generalized Predictive Control (GPC). Computationally efficient Fast DMC (FDMC) and Fast GPC (FGPC) algorithms are derived in which the values of the manipulated variables are calculated from uncomplicated explicit formulas. To demonstrate effectiveness of the discussed algorithms, two emulated benchmark processes and a laboratory servo are considered. The influence of some tuning parameters on algorithms' calculation time is studied. It is shown that for short sampling periods the classical DMC and GPC algorithms fail to work since calculations last longer than the sampling period, which is unacceptable. Conversely, the FDMC and FGPC algorithms require only hundreds or tens of microseconds and single microseconds, respectively. Hence, proposed algorithms may be used for very fast processes, with very short sampling time. |
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| AbstractList | This paper describes fast versions of model predictive control (MPC) algorithms and their practical implementation using the STM32 ARM microcontroller. Two MPC algorithms are considered: Dynamic Matrix Control (DMC) and Generalized Predictive Control (GPC). Computationally efficient Fast DMC (FDMC) and Fast GPC (FGPC) algorithms are derived in which the values of the manipulated variables are calculated from uncomplicated explicit formulas. To demonstrate effectiveness of the discussed algorithms, two emulated benchmark processes and a laboratory servo are considered. The influence of some tuning parameters on algorithms’ calculation time is studied. It is shown that for short sampling periods the classical DMC and GPC algorithms fail to work since calculations last longer than the sampling period, which is unacceptable. Conversely, the FDMC and FGPC algorithms require only hundreds or tens of microseconds and single microseconds, respectively. Hence, proposed algorithms may be used for very fast processes, with very short sampling time. |
| Author | Lawrynczuk, Maciej Chaber, Patryk |
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| SubjectTerms | Algorithms Computational modeling Heuristic algorithms Mathematical model Mathematical models Microcontrollers model predictive control Monte Carlo methods Prediction algorithms Predictive control Process control Sampling |
| Title | Fast Analytical Model Predictive Controllers and Their Implementation for STM32 ARM Microcontroller |
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