Saturday , March 2 2024

Affordable Control Platform with MPC Applications

Álan C. E SOUSA1, Valter J. S. LEITE1*, Ignacio RUBIO SCOLA2
1 Centro Federal de Educação Tecnológica de Minas Gerais (CEFET-MG, campus Divinópolis),
Rua Alvares de Azevedo, 400, Divinópolis, 35.503-822, Brazil
2 Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas, CIFASIS-CONICET,
Ocampo y Esmeralda, S2000EZP, Rosario, Argentina, (*Corresponding author),

ABSTRACT: This paper presents a control platform developed to interface with various hardware, allowing the design and rapid implementation even of advanced controllers, both on academic and industrial systems. The code of the controllers is written in the open-source Python language, facilitating the translation of code usually written in commercial software. The proposed platform can use from Arduinos to Programmable Logic Computers (PLCs). Beyond the research and tests on industrial facilities, the simplicity of the proposed platform allows its use also for educational and training purposes. Therefore, the proposed platform can help students focus on system analysis and control theory instead of hardware interfacing issues, while using low cost hardware. Developed in a client-server scheme, the platform can run in affordable computers while taking advantage of high-level mathematical and graphical tools available in Python language, allowing rapid implementation of advanced controllers. The use of this platform is illustrated with an implementation of a model predictive control (MPC) of a level control in a laboratory-scale process. A PLC is used to take the level measures, to dispatch control signals, and also for interlocking secure tasks. The controller runs on a Raspberry Pi computer that communicates with the PLC through an ethernet link.

KEYWORDS: Control platform, MPC, Affordable computer, Optimal control.


Álan C. E SOUSA, Valter J. S. LEITE, Ignacio RUBIO SCOLA, Affordable Control Platform with MPC Application, Studies in Informatics and Control, ISSN 1220-1766, vol. 27(3), pp. 265-274, 2018.