Keywords

Benchmark, Dynamics, PID tuning, Model predictive control, Microcontroller

Abstract

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.

Original Publication Citation

https://www.sciencedirect.com/science/article/abs/pii/S0098135419310129

Document Type

Peer-Reviewed Article

Publication Date

2020-04-06

Publisher

Elsevier

Language

English

College

Ira A. Fulton College of Engineering and Technology

Department

Chemical Engineering

University Standing at Time of Publication

Associate Professor

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