A Fuzzy-Descriptor-System-Based Control Design Methodology for Rotary Inverted Pendulum

This paper presents a control design methodology for rotary inverted pendulum based on a fuzzy descriptor system. In this methodology, the nonlinear dynamics of the rotary inverted pendulum is exactly presented by a fuzzy descriptor system. After that, based on the fuzzy descriptor system and applying the Lyapunov stability theorem, a decay rate fuzzy control design is proposed for stabilizing the rotary inverted pendulum. Furthermore, for practical application, the constraint of input voltage is also considered in the control design. The control design is represented in terms of linear matrix inequality (LMI) conditions which can be efficiently solved by the LMI solvers of MATLAB Robust Control Toolbox. Finally, simulation and experiment results are provided to demonstrate the effectiveness of the proposed fuzzy-descriptor-system-based control design methodology.

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Publication Details

Published
2024-08-10
DOI
https://doi.org/10.1109/ifuzzy63051.2024.10662878
Primary Topic
Fuzzy Logic and Control Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

A Fuzzy-Descriptor-System-Based Control Design Methodology for Rotary Inverted Pendulum

Ying‐Jen Chen, Mei Yamamoto, Kazuo Tanaka, Nanami Mori
Fuzzy Logic and Control Systems
article

A Fuzzy-Descriptor-System-Based Control Design Methodology for Rotary Inverted Pendulum

Ying‐Jen Chen, Mei Yamamoto, Kazuo Tanaka, Nanami Mori
article en

Abstract

This paper presents a control design methodology for rotary inverted pendulum based on a fuzzy descriptor system. In this methodology, the nonlinear dynamics of the rotary inverted pendulum is exactly presented by a fuzzy descriptor system. After that, based on the fuzzy descriptor system and applying the Lyapunov stability theorem, a decay rate fuzzy control design is proposed for stabilizing the rotary inverted pendulum. Furthermore, for practical application, the constraint of input voltage is also considered in the control design. The control design is represented in terms of linear matrix inequality (LMI) conditions which can be efficiently solved by the LMI solvers of MATLAB Robust Control Toolbox. Finally, simulation and experiment results are provided to demonstrate the effectiveness of the proposed fuzzy-descriptor-system-based control design methodology.

University of Electro-Communications (JP), Yuan Ze University (TW)
Affordable and clean energy
Openalex Percentile: Top 87%
Fuzzy Logic and Control Systems
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