A novel intelligent control of discrete-time nonlinear systems in the presence of output saturation

In this paper, a model free control method for a class of discrete time nonlinear systems is introduced. A type-3 fuzzy system estimates the unknown parameters required by the control system. The control system only uses the input and output data of the plant and therefore does not need to know its mathematical equations. On the other hand, the phenomenon of output saturation is a challenging problem for all control systems, addressed in detail in the proposed method. The convergence of the proposed method is guaranteed, and the control system is very robust in the face of changes in the dynamics of the plant. The simulation results on discrete-time nonlinear systems show that the proposed method is very accurate despite the high speed of convergence. In addition, the proposed method is robust for modeling uncertainties and has a better root mean square error and step response time compared to the other methods. Also, a comparison has been made between type-1 to type-3 fuzzy systems and control system based on trial and error, which shows firstly the importance of the presence of fuzzy system and secondly the superiority of type-3 fuzzy system compared to the other two types.

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Publication Details

Journal
Heliyon
Published
2024-09-21
DOI
https://doi.org/10.1016/j.heliyon.2024.e38279
Citations
4
Primary Topic
Adaptive Control of Nonlinear Systems
Type
article
Field-Weighted Citation Impact
1.31
Controls
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article

A novel intelligent control of discrete-time nonlinear systems in the presence of output saturation

Ying Dai, Ebrahim Ghaderpour, Ardashir Mohammadzadeh, Xuejun Zhou et al.
4 citations
Heliyon
Adaptive Control of Nonlinear Systems
1.31
article

A novel intelligent control of discrete-time nonlinear systems in the presence of output saturation

Ying Dai, Ebrahim Ghaderpour, Ardashir Mohammadzadeh, Xuejun Zhou, Pierpaolo D'Urso
article en
4 citations

Abstract

In this paper, a model free control method for a class of discrete time nonlinear systems is introduced. A type-3 fuzzy system estimates the unknown parameters required by the control system. The control system only uses the input and output data of the plant and therefore does not need to know its mathematical equations. On the other hand, the phenomenon of output saturation is a challenging problem for all control systems, addressed in detail in the proposed method. The convergence of the proposed method is guaranteed, and the control system is very robust in the face of changes in the dynamics of the plant. The simulation results on discrete-time nonlinear systems show that the proposed method is very accurate despite the high speed of convergence. In addition, the proposed method is robust for modeling uncertainties and has a better root mean square error and step response time compared to the other methods. Also, a comparison has been made between type-1 to type-3 fuzzy systems and control system based on trial and error, which shows firstly the importance of the presence of fuzzy system and secondly the superiority of type-3 fuzzy system compared to the other two types.

HeliyonVol. 10(19)
Sakarya University (TR), Shenyang University of Technology (CN), Yan'an University (CN), Sapienza University of Rome (IT)
Openalex Percentile: Top 19%
Adaptive Control of Nonlinear Systems
1.31
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