Adaptive PID controller based on model predictive control

Ahmed A. Abdelrauf; M. Abdel-Geliel; E. Zakzouk

doi:10.1109/ECC.2016.7810378

Adaptive PID controller based on model predictive control

Ahmed A. Abdelrauf, M. Abdel-Geliel, E. Zakzouk

Department of Electrical and Electronic Engineering

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

11 Citations (Scopus)

Abstract

Model Predictive Control (MPC) is very suitable controller for many industrial applications especially for constrained systems. However, it requires high computation burden. On the other side, PID controller is simple and popular for industrial applications in particular for Single Input Single Output (SISO) systems but it is difficult to be tuned especially for constrained systems. To gain the benefits of the two controllers and reduce their limitations, a hierarchical control structure (two levels) is proposed. The algorithm concept focuses on the adaptation of PID controller parameters (lower level) according to the MPC performance (higher level). The algorithm is tested on two constrained systems; separately excited DC motor as a SISO system and three tank system as Multi Input Multi Output (MIMO) benchmark system.

Original language	English
Title of host publication	2016 European Control Conference, ECC 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	746-751
Number of pages	6
ISBN (Electronic)	9781509025916
DOIs	https://doi.org/10.1109/ECC.2016.7810378
Publication status	Published - 6 Jan 2017
Event	2016 European Control Conference, ECC 2016 - Aalborg, Denmark Duration: 29 Jun 2016 → 1 Jul 2016

Publication series

Name	2016 European Control Conference, ECC 2016

Conference

Conference	2016 European Control Conference, ECC 2016
Country/Territory	Denmark
City	Aalborg
Period	29/06/16 → 1/07/16

ASJC Scopus subject areas

Control and Systems Engineering
Control and Optimization

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10.1109/ECC.2016.7810378

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title = "Adaptive PID controller based on model predictive control",

abstract = "Model Predictive Control (MPC) is very suitable controller for many industrial applications especially for constrained systems. However, it requires high computation burden. On the other side, PID controller is simple and popular for industrial applications in particular for Single Input Single Output (SISO) systems but it is difficult to be tuned especially for constrained systems. To gain the benefits of the two controllers and reduce their limitations, a hierarchical control structure (two levels) is proposed. The algorithm concept focuses on the adaptation of PID controller parameters (lower level) according to the MPC performance (higher level). The algorithm is tested on two constrained systems; separately excited DC motor as a SISO system and three tank system as Multi Input Multi Output (MIMO) benchmark system.",

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Abdelrauf, AA, Abdel-Geliel, M & Zakzouk, E 2017, Adaptive PID controller based on model predictive control. in 2016 European Control Conference, ECC 2016., 7810378, 2016 European Control Conference, ECC 2016, Institute of Electrical and Electronics Engineers Inc., pp. 746-751, 2016 European Control Conference, ECC 2016, Aalborg, Denmark, 29/06/16. https://doi.org/10.1109/ECC.2016.7810378

Adaptive PID controller based on model predictive control. / Abdelrauf, Ahmed A.; Abdel-Geliel, M.; Zakzouk, E.
2016 European Control Conference, ECC 2016. Institute of Electrical and Electronics Engineers Inc., 2017. p. 746-751 7810378 (2016 European Control Conference, ECC 2016).

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

TY - GEN

T1 - Adaptive PID controller based on model predictive control

AU - Abdelrauf, Ahmed A.

AU - Abdel-Geliel, M.

AU - Zakzouk, E.

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AB - Model Predictive Control (MPC) is very suitable controller for many industrial applications especially for constrained systems. However, it requires high computation burden. On the other side, PID controller is simple and popular for industrial applications in particular for Single Input Single Output (SISO) systems but it is difficult to be tuned especially for constrained systems. To gain the benefits of the two controllers and reduce their limitations, a hierarchical control structure (two levels) is proposed. The algorithm concept focuses on the adaptation of PID controller parameters (lower level) according to the MPC performance (higher level). The algorithm is tested on two constrained systems; separately excited DC motor as a SISO system and three tank system as Multi Input Multi Output (MIMO) benchmark system.

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Adaptive PID controller based on model predictive control

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