Performance enhancement of multivariable model reference optimal adaptive motor speed controller using error-dependent hyperbolic gain functions
The main contribution of this paper is to formulate a robust-adaptive and stable state-space speed control strategy for DC motors. The linear-quadratic-integral (LQI) controller is utilized as the baseline controller for optimal speed-regulation, accurate reference-tracking and elimination of steady...
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Online Access: | http://dx.doi.org/10.1080/00051144.2019.1688508 |
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doaj-3050d439cbbb462e94d07a794cac68632020-11-25T02:00:06ZengTaylor & Francis GroupAutomatika0005-11441848-33802020-01-0161111713110.1080/00051144.2019.16885081688508Performance enhancement of multivariable model reference optimal adaptive motor speed controller using error-dependent hyperbolic gain functionsOmer Saleem0Mohsin Rizwan1Khalid Mahmood-ul-Hasan2Muaaz Ahmad3Department of Electrical Engineering, National University of Computer and Emerging SciencesUniversity of Engineering & TechnologyUniversity of Engineering and TechnologyDepartment of Electrical Engineering, National University of Computer and Emerging SciencesThe main contribution of this paper is to formulate a robust-adaptive and stable state-space speed control strategy for DC motors. The linear-quadratic-integral (LQI) controller is utilized as the baseline controller for optimal speed-regulation, accurate reference-tracking and elimination of steady-state fluctuations in the motor’s response. To reject the influence of modelling errors, the LQI controller is augmented with a Lyapunov-based model reference adaptation system (MRAS) that adaptively modulates the controller gains while maintaining the asymptotic stability of the controller. To further enhance the system’s robustness against parametric uncertainties, the adaptation gains of MRAS online gain-adjustment law are dynamically adjusted, after every sampling interval, using smooth hyperbolic functions of motor’s speed-error. This modification significantly improves the system’s response-speed and damping against oscillations, while ensuring its stability under all operating conditions. It dynamically re-configures the control-input trajectory to enhance the system’s immunity against the detrimental effects of random faults occurring in practical motorized systems such as bounded impulsive-disturbances, modelling errors, and abrupt load–torque variations. The efficacy of the proposed control strategy is validated by conducting credible hardware-in-the-loop experiments on QNET 2.0 DC Motor Board. The experimental results successfully validate the superior tracking accuracy and disturbance-rejection capability of the proposed control strategy as compared to other controller variants benchmarked in this article.http://dx.doi.org/10.1080/00051144.2019.1688508model reference adaptive controllqi controllyapunov theoryhyperbolic functionqnet 2.0 dc motor board |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Omer Saleem Mohsin Rizwan Khalid Mahmood-ul-Hasan Muaaz Ahmad |
spellingShingle |
Omer Saleem Mohsin Rizwan Khalid Mahmood-ul-Hasan Muaaz Ahmad Performance enhancement of multivariable model reference optimal adaptive motor speed controller using error-dependent hyperbolic gain functions Automatika model reference adaptive control lqi control lyapunov theory hyperbolic function qnet 2.0 dc motor board |
author_facet |
Omer Saleem Mohsin Rizwan Khalid Mahmood-ul-Hasan Muaaz Ahmad |
author_sort |
Omer Saleem |
title |
Performance enhancement of multivariable model reference optimal adaptive motor speed controller using error-dependent hyperbolic gain functions |
title_short |
Performance enhancement of multivariable model reference optimal adaptive motor speed controller using error-dependent hyperbolic gain functions |
title_full |
Performance enhancement of multivariable model reference optimal adaptive motor speed controller using error-dependent hyperbolic gain functions |
title_fullStr |
Performance enhancement of multivariable model reference optimal adaptive motor speed controller using error-dependent hyperbolic gain functions |
title_full_unstemmed |
Performance enhancement of multivariable model reference optimal adaptive motor speed controller using error-dependent hyperbolic gain functions |
title_sort |
performance enhancement of multivariable model reference optimal adaptive motor speed controller using error-dependent hyperbolic gain functions |
publisher |
Taylor & Francis Group |
series |
Automatika |
issn |
0005-1144 1848-3380 |
publishDate |
2020-01-01 |
description |
The main contribution of this paper is to formulate a robust-adaptive and stable state-space speed control strategy for DC motors. The linear-quadratic-integral (LQI) controller is utilized as the baseline controller for optimal speed-regulation, accurate reference-tracking and elimination of steady-state fluctuations in the motor’s response. To reject the influence of modelling errors, the LQI controller is augmented with a Lyapunov-based model reference adaptation system (MRAS) that adaptively modulates the controller gains while maintaining the asymptotic stability of the controller. To further enhance the system’s robustness against parametric uncertainties, the adaptation gains of MRAS online gain-adjustment law are dynamically adjusted, after every sampling interval, using smooth hyperbolic functions of motor’s speed-error. This modification significantly improves the system’s response-speed and damping against oscillations, while ensuring its stability under all operating conditions. It dynamically re-configures the control-input trajectory to enhance the system’s immunity against the detrimental effects of random faults occurring in practical motorized systems such as bounded impulsive-disturbances, modelling errors, and abrupt load–torque variations. The efficacy of the proposed control strategy is validated by conducting credible hardware-in-the-loop experiments on QNET 2.0 DC Motor Board. The experimental results successfully validate the superior tracking accuracy and disturbance-rejection capability of the proposed control strategy as compared to other controller variants benchmarked in this article. |
topic |
model reference adaptive control lqi control lyapunov theory hyperbolic function qnet 2.0 dc motor board |
url |
http://dx.doi.org/10.1080/00051144.2019.1688508 |
work_keys_str_mv |
AT omersaleem performanceenhancementofmultivariablemodelreferenceoptimaladaptivemotorspeedcontrollerusingerrordependenthyperbolicgainfunctions AT mohsinrizwan performanceenhancementofmultivariablemodelreferenceoptimaladaptivemotorspeedcontrollerusingerrordependenthyperbolicgainfunctions AT khalidmahmoodulhasan performanceenhancementofmultivariablemodelreferenceoptimaladaptivemotorspeedcontrollerusingerrordependenthyperbolicgainfunctions AT muaazahmad performanceenhancementofmultivariablemodelreferenceoptimaladaptivemotorspeedcontrollerusingerrordependenthyperbolicgainfunctions |
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1724962566405357568 |