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Benchmark temperature microcontroller for process dynamics and control.
- Source :
-
Computers & Chemical Engineering . Apr2020, Vol. 135, pN.PAG-N.PAG. 1p. - Publication Year :
- 2020
-
Abstract
- • Physics-based and data-driven modeling approaches are quantified with the TCLab. • A PID tuning method is proposed to replay disturbances from closed-loop data. • Model predictive control is benchmarked with three standard models. • Real-time results are presented to motivate further benchmark studies. Standard benchmarks are important repositories to establish comparisons between competing model and control methods, especially when a new method is proposed. This paper presents details of an Arduino micro-controller temperature control lab as a benchmark for modeling and control methods. As opposed to simulation studies, a physical benchmark considers real process characteristics such as the requirement to meet a cycle time, discrete sampling intervals, communication overhead with the process, and model mismatch. An example case study of the benchmark is quantifying an optimization approach for a PID controller with 5.4% improved performance. A multivariate example shows the quantified performance improvement by using model predictive control with a physics-based model, an autoregressive time series model, and a Hammerstein model with an artificial neural network to capture the static nonlinearity. These results demonstrate the potential of a hardware benchmark for transient modeling and regulatory or advanced control methods. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00981354
- Volume :
- 135
- Database :
- Academic Search Index
- Journal :
- Computers & Chemical Engineering
- Publication Type :
- Academic Journal
- Accession number :
- 142002825
- Full Text :
- https://doi.org/10.1016/j.compchemeng.2020.106736