Comparison of the performance and energy consumption index of model-based controllers

Luis I. Minchala-Avila; Kenneth Palacio-Baus; Juan P. Ortiz; Juan D. Valladolid; Juan Ortega

doi:10.1109/ETCM.2016.7750825

Comparison of the performance and energy consumption index of model-based controllers

Luis I. Minchala-Avila, Kenneth Palacio-Baus, Juan P. Ortiz, Juan D. Valladolid, Juan Ortega

Research Group in Transportation Engineering (GIIT)

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

14 Scopus citations

Abstract

This paper presents a comparison of the performance of different control algorithms in two types of systems; one exhibiting fast dynamics and the other slow dynamics. The first control system regulates the speed of a DC motor, while the second control system regulates the temperature of an electrical heater. This systems' performance comparison pretends to evaluate the energy consumption, as well as the controllers' transient response in order to identify the best control strategy for each system. System models are obtained through the responses to a pseudorandom binary signal (PRBS) and the least squares fit method using an auto-regressive model with an exogenous variable (ARX). The implemented control algorithms used in this study are: Pole placement regulator (state-space controller) with integral error processing, auto-tunable proportional-integral-derivative (PID) controller, neural PID controller, unconstrained model predictive control (MPC), fuzzy PID controller, neuro-fuzzy controller, bayesian controller and an optimal quadratic regulator (LQR). A detailed analysis of the performance and energy consumption index is performed, that allow the categorization of the control strategies in accordance with their performance.

Translated title of the contribution	Comparación del rendimiento y del índice de consumo de energía de los controladores basados en modelos
Original language	English
Title of host publication	2016 IEEE Ecuador Technical Chapters Meeting, ETCM 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781509016297
DOIs	https://doi.org/10.1109/ETCM.2016.7750825
State	Published - 21 Nov 2016
Event	2016 IEEE Ecuador Technical Chapters Meeting, ETCM 2016 - Quito, Ecuador Duration: 12 Oct 2016 → 14 Oct 2016

Publication series

Name	2016 IEEE Ecuador Technical Chapters Meeting, ETCM 2016

Conference

Conference	2016 IEEE Ecuador Technical Chapters Meeting, ETCM 2016
Abbreviated title	ETCM 2016
Country/Territory	Ecuador
City	Quito
Period	12/10/16 → 14/10/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Keywords

DC motor speed control
Digital controller
model
performance index
temperature control

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/ETCM.2016.7750825

Cite this

Minchala-Avila, L. I., Palacio-Baus, K., Ortiz, J. P., Valladolid, J. D., & Ortega, J. (2016). Comparison of the performance and energy consumption index of model-based controllers. In 2016 IEEE Ecuador Technical Chapters Meeting, ETCM 2016 Article 7750825 (2016 IEEE Ecuador Technical Chapters Meeting, ETCM 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ETCM.2016.7750825

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abstract = "This paper presents a comparison of the performance of different control algorithms in two types of systems; one exhibiting fast dynamics and the other slow dynamics. The first control system regulates the speed of a DC motor, while the second control system regulates the temperature of an electrical heater. This systems' performance comparison pretends to evaluate the energy consumption, as well as the controllers' transient response in order to identify the best control strategy for each system. System models are obtained through the responses to a pseudorandom binary signal (PRBS) and the least squares fit method using an auto-regressive model with an exogenous variable (ARX). The implemented control algorithms used in this study are: Pole placement regulator (state-space controller) with integral error processing, auto-tunable proportional-integral-derivative (PID) controller, neural PID controller, unconstrained model predictive control (MPC), fuzzy PID controller, neuro-fuzzy controller, bayesian controller and an optimal quadratic regulator (LQR). A detailed analysis of the performance and energy consumption index is performed, that allow the categorization of the control strategies in accordance with their performance.",

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Minchala-Avila, LI, Palacio-Baus, K, Ortiz, JP , Valladolid, JD & Ortega, J 2016, Comparison of the performance and energy consumption index of model-based controllers. in 2016 IEEE Ecuador Technical Chapters Meeting, ETCM 2016., 7750825, 2016 IEEE Ecuador Technical Chapters Meeting, ETCM 2016, Institute of Electrical and Electronics Engineers Inc., 2016 IEEE Ecuador Technical Chapters Meeting, ETCM 2016, Quito, Ecuador, 12/10/16. https://doi.org/10.1109/ETCM.2016.7750825

Comparison of the performance and energy consumption index of model-based controllers. / Minchala-Avila, Luis I.; Palacio-Baus, Kenneth; Ortiz, Juan P. et al.
2016 IEEE Ecuador Technical Chapters Meeting, ETCM 2016. Institute of Electrical and Electronics Engineers Inc., 2016. 7750825 (2016 IEEE Ecuador Technical Chapters Meeting, ETCM 2016).

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

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AB - This paper presents a comparison of the performance of different control algorithms in two types of systems; one exhibiting fast dynamics and the other slow dynamics. The first control system regulates the speed of a DC motor, while the second control system regulates the temperature of an electrical heater. This systems' performance comparison pretends to evaluate the energy consumption, as well as the controllers' transient response in order to identify the best control strategy for each system. System models are obtained through the responses to a pseudorandom binary signal (PRBS) and the least squares fit method using an auto-regressive model with an exogenous variable (ARX). The implemented control algorithms used in this study are: Pole placement regulator (state-space controller) with integral error processing, auto-tunable proportional-integral-derivative (PID) controller, neural PID controller, unconstrained model predictive control (MPC), fuzzy PID controller, neuro-fuzzy controller, bayesian controller and an optimal quadratic regulator (LQR). A detailed analysis of the performance and energy consumption index is performed, that allow the categorization of the control strategies in accordance with their performance.

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Minchala-Avila LI, Palacio-Baus K, Ortiz JP , Valladolid JD, Ortega J. Comparison of the performance and energy consumption index of model-based controllers. In 2016 IEEE Ecuador Technical Chapters Meeting, ETCM 2016. Institute of Electrical and Electronics Engineers Inc. 2016. 7750825. (2016 IEEE Ecuador Technical Chapters Meeting, ETCM 2016). doi: 10.1109/ETCM.2016.7750825

Comparison of the performance and energy consumption index of model-based controllers

Abstract

Publication series

Conference

Bibliographical note

Keywords

UN SDGs

Access to Document

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