Multi-Loop Model Reference Proportional Integral Derivative Controls: Design and Performance Evaluations
Due to unpredictable and fluctuating conditions in real-world control system applications, disturbance rejection is a substantial factor in robust control performance. The inherent disturbance rejection capacity of classical closed loop control systems is limited, and an increase in disturbance reje...
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doaj-7d70e0f535374dd389ffa738f885795f2020-11-25T02:38:44ZengMDPI AGAlgorithms1999-48932020-02-011323810.3390/a13020038a13020038Multi-Loop Model Reference Proportional Integral Derivative Controls: Design and Performance EvaluationsBaris Baykant Alagoz0Aleksei Tepljakov1Eduard Petlenkov2Celaleddin Yeroglu3Department of Computer Engineering, Inonu University, 44000 Malatya, TurkeyDepartment of Computer Systems, Tallinn University of Technology, 12616 Tallinn, EstoniaDepartment of Computer Systems, Tallinn University of Technology, 12616 Tallinn, EstoniaDepartment of Computer Systems, Tallinn University of Technology, 12616 Tallinn, EstoniaDue to unpredictable and fluctuating conditions in real-world control system applications, disturbance rejection is a substantial factor in robust control performance. The inherent disturbance rejection capacity of classical closed loop control systems is limited, and an increase in disturbance rejection performance of single-loop control systems affects the set-point control performance. Multi-loop control structures, which involve model reference control loops, can enhance the inherent disturbance rejection capacity of classical control loops without degrading set-point control performance; while the classical closed Proportional Integral Derivative (PID) control loop deals with stability and set-point control, the additional model reference control loop performs disturbance rejection control. This adaptive disturbance rejection, which does not influence set-point control performance, is achieved by selecting reference models as transfer functions of real control systems. This study investigates six types of multi-loop model reference (ML-MR) control structures for PID control loops and presents straightforward design schemes to enhance the disturbance rejection control performance of existing PID control loops. For this purpose, linear and non-linear ML-MR control structures are introduced, and their control performance improvements and certain inherent drawbacks of these structures are discussed. Design examples demonstrate the benefits of the ML-MR control structures for disturbance rejection performance improvement of PID control loops without severely deteriorating their set-point performance.https://www.mdpi.com/1999-4893/13/2/38multi-loop model reference controlpid controllersdisturbance rejection control |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Baris Baykant Alagoz Aleksei Tepljakov Eduard Petlenkov Celaleddin Yeroglu |
spellingShingle |
Baris Baykant Alagoz Aleksei Tepljakov Eduard Petlenkov Celaleddin Yeroglu Multi-Loop Model Reference Proportional Integral Derivative Controls: Design and Performance Evaluations Algorithms multi-loop model reference control pid controllers disturbance rejection control |
author_facet |
Baris Baykant Alagoz Aleksei Tepljakov Eduard Petlenkov Celaleddin Yeroglu |
author_sort |
Baris Baykant Alagoz |
title |
Multi-Loop Model Reference Proportional Integral Derivative Controls: Design and Performance Evaluations |
title_short |
Multi-Loop Model Reference Proportional Integral Derivative Controls: Design and Performance Evaluations |
title_full |
Multi-Loop Model Reference Proportional Integral Derivative Controls: Design and Performance Evaluations |
title_fullStr |
Multi-Loop Model Reference Proportional Integral Derivative Controls: Design and Performance Evaluations |
title_full_unstemmed |
Multi-Loop Model Reference Proportional Integral Derivative Controls: Design and Performance Evaluations |
title_sort |
multi-loop model reference proportional integral derivative controls: design and performance evaluations |
publisher |
MDPI AG |
series |
Algorithms |
issn |
1999-4893 |
publishDate |
2020-02-01 |
description |
Due to unpredictable and fluctuating conditions in real-world control system applications, disturbance rejection is a substantial factor in robust control performance. The inherent disturbance rejection capacity of classical closed loop control systems is limited, and an increase in disturbance rejection performance of single-loop control systems affects the set-point control performance. Multi-loop control structures, which involve model reference control loops, can enhance the inherent disturbance rejection capacity of classical control loops without degrading set-point control performance; while the classical closed Proportional Integral Derivative (PID) control loop deals with stability and set-point control, the additional model reference control loop performs disturbance rejection control. This adaptive disturbance rejection, which does not influence set-point control performance, is achieved by selecting reference models as transfer functions of real control systems. This study investigates six types of multi-loop model reference (ML-MR) control structures for PID control loops and presents straightforward design schemes to enhance the disturbance rejection control performance of existing PID control loops. For this purpose, linear and non-linear ML-MR control structures are introduced, and their control performance improvements and certain inherent drawbacks of these structures are discussed. Design examples demonstrate the benefits of the ML-MR control structures for disturbance rejection performance improvement of PID control loops without severely deteriorating their set-point performance. |
topic |
multi-loop model reference control pid controllers disturbance rejection control |
url |
https://www.mdpi.com/1999-4893/13/2/38 |
work_keys_str_mv |
AT barisbaykantalagoz multiloopmodelreferenceproportionalintegralderivativecontrolsdesignandperformanceevaluations AT alekseitepljakov multiloopmodelreferenceproportionalintegralderivativecontrolsdesignandperformanceevaluations AT eduardpetlenkov multiloopmodelreferenceproportionalintegralderivativecontrolsdesignandperformanceevaluations AT celaleddinyeroglu multiloopmodelreferenceproportionalintegralderivativecontrolsdesignandperformanceevaluations |
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1724790019558735872 |