Nonlinear Identification and Position Control of a Pneumatic System

Víctor Huilcapi; Ricardo Cajo; Jorge Orellana; Alex Cascante

doi:10.1007/978-3-031-24327-1_11

Nonlinear Identification and Position Control of a Pneumatic System

Víctor Huilcapi, Ricardo Cajo, Jorge Orellana, Alex Cascante

Control Systems and Robotics Research Group (GISCOR)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

In this work a pneumatic positioning system is studied. The system presents high nonlinearities since it is subjected to static friction, dead bands, and dead times. Firstly, the system identification is done using nonlinear identification based on the Hammerstein-Wiener model. Then, some control strategies such as Proportional-Integral-Derivative (PID) controller, Fuzzy-PID controller and Model Predictive Control (MPC) are designed to handle these nonlinearities. The main goal is to control the displacement of the pneumatic cylinder to reach any position or trajectory tracking in the shortest possible time and with the least steady state error. The results show that the Hammerstein-Wiener model identified for the system satisfactorily characterizes its nonlinear dynamics. The MPC is more efficient to control the system compared to the other controllers as it has less steady state error and stabilizes the system faster.

Original language	English
Title of host publication	Intelligent Technologies
Subtitle of host publication	Design and Applications for Society - Proceedings of CITIS 2022
Editors	Vladimir Robles-Bykbaev, Josefa Mula, Gilberto Reynoso-Meza
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	127-138
Number of pages	12
ISBN (Print)	9783031243264
DOIs	https://doi.org/10.1007/978-3-031-24327-1_11
State	Published - 2023
Event	8th International Conference on Science, Technology and Innovation for Society, CITIS 2022 - Guayaquil, Ecuador Duration: 22 Jun 2022 → 24 Jun 2022

Publication series

Name	Lecture Notes in Networks and Systems
Volume	607 LNNS
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	8th International Conference on Science, Technology and Innovation for Society, CITIS 2022
Country/Territory	Ecuador
City	Guayaquil
Period	22/06/22 → 24/06/22

Bibliographical note

Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

Fuzzy-PID
Model Predictive Control (MPC)
Nonlinear Identification
PID
Pneumatic system

Access to Document

10.1007/978-3-031-24327-1_11

Cite this

Huilcapi, V., Cajo, R., Orellana, J., & Cascante, A. (2023). Nonlinear Identification and Position Control of a Pneumatic System. In V. Robles-Bykbaev, J. Mula, & G. Reynoso-Meza (Eds.), Intelligent Technologies: Design and Applications for Society - Proceedings of CITIS 2022 (pp. 127-138). (Lecture Notes in Networks and Systems; Vol. 607 LNNS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-24327-1_11

Huilcapi, Víctor ; Cajo, Ricardo ; Orellana, Jorge et al. / Nonlinear Identification and Position Control of a Pneumatic System. Intelligent Technologies: Design and Applications for Society - Proceedings of CITIS 2022. editor / Vladimir Robles-Bykbaev ; Josefa Mula ; Gilberto Reynoso-Meza. Springer Science and Business Media Deutschland GmbH, 2023. pp. 127-138 (Lecture Notes in Networks and Systems).

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abstract = "In this work a pneumatic positioning system is studied. The system presents high nonlinearities since it is subjected to static friction, dead bands, and dead times. Firstly, the system identification is done using nonlinear identification based on the Hammerstein-Wiener model. Then, some control strategies such as Proportional-Integral-Derivative (PID) controller, Fuzzy-PID controller and Model Predictive Control (MPC) are designed to handle these nonlinearities. The main goal is to control the displacement of the pneumatic cylinder to reach any position or trajectory tracking in the shortest possible time and with the least steady state error. The results show that the Hammerstein-Wiener model identified for the system satisfactorily characterizes its nonlinear dynamics. The MPC is more efficient to control the system compared to the other controllers as it has less steady state error and stabilizes the system faster.",

keywords = "Fuzzy-PID, Model Predictive Control (MPC), Nonlinear Identification, PID, Pneumatic system",

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Huilcapi, V, Cajo, R, Orellana, J & Cascante, A 2023, Nonlinear Identification and Position Control of a Pneumatic System. in V Robles-Bykbaev, J Mula & G Reynoso-Meza (eds), Intelligent Technologies: Design and Applications for Society - Proceedings of CITIS 2022. Lecture Notes in Networks and Systems, vol. 607 LNNS, Springer Science and Business Media Deutschland GmbH, pp. 127-138, 8th International Conference on Science, Technology and Innovation for Society, CITIS 2022, Guayaquil, Ecuador, 22/06/22. https://doi.org/10.1007/978-3-031-24327-1_11

Nonlinear Identification and Position Control of a Pneumatic System. / Huilcapi, Víctor; Cajo, Ricardo; Orellana, Jorge et al.
Intelligent Technologies: Design and Applications for Society - Proceedings of CITIS 2022. ed. / Vladimir Robles-Bykbaev; Josefa Mula; Gilberto Reynoso-Meza. Springer Science and Business Media Deutschland GmbH, 2023. p. 127-138 (Lecture Notes in Networks and Systems; Vol. 607 LNNS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Nonlinear Identification and Position Control of a Pneumatic System

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AU - Cajo, Ricardo

AU - Orellana, Jorge

AU - Cascante, Alex

PY - 2023

Y1 - 2023

N2 - In this work a pneumatic positioning system is studied. The system presents high nonlinearities since it is subjected to static friction, dead bands, and dead times. Firstly, the system identification is done using nonlinear identification based on the Hammerstein-Wiener model. Then, some control strategies such as Proportional-Integral-Derivative (PID) controller, Fuzzy-PID controller and Model Predictive Control (MPC) are designed to handle these nonlinearities. The main goal is to control the displacement of the pneumatic cylinder to reach any position or trajectory tracking in the shortest possible time and with the least steady state error. The results show that the Hammerstein-Wiener model identified for the system satisfactorily characterizes its nonlinear dynamics. The MPC is more efficient to control the system compared to the other controllers as it has less steady state error and stabilizes the system faster.

AB - In this work a pneumatic positioning system is studied. The system presents high nonlinearities since it is subjected to static friction, dead bands, and dead times. Firstly, the system identification is done using nonlinear identification based on the Hammerstein-Wiener model. Then, some control strategies such as Proportional-Integral-Derivative (PID) controller, Fuzzy-PID controller and Model Predictive Control (MPC) are designed to handle these nonlinearities. The main goal is to control the displacement of the pneumatic cylinder to reach any position or trajectory tracking in the shortest possible time and with the least steady state error. The results show that the Hammerstein-Wiener model identified for the system satisfactorily characterizes its nonlinear dynamics. The MPC is more efficient to control the system compared to the other controllers as it has less steady state error and stabilizes the system faster.

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Huilcapi V, Cajo R, Orellana J, Cascante A. Nonlinear Identification and Position Control of a Pneumatic System. In Robles-Bykbaev V, Mula J, Reynoso-Meza G, editors, Intelligent Technologies: Design and Applications for Society - Proceedings of CITIS 2022. Springer Science and Business Media Deutschland GmbH. 2023. p. 127-138. (Lecture Notes in Networks and Systems). doi: 10.1007/978-3-031-24327-1_11

Nonlinear Identification and Position Control of a Pneumatic System

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Keywords

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