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Robust-optimal control of rotary inverted pendulum control through fuzzy descriptor-based techniques
by
Bui, Ngoc-Tam
, Pham, Duc-Binh
, Dao, Quy-Thinh
, Nguyen, Thi-Van-Anh
in
639/166
/ 639/166/988
/ Adaptability
/ Controllers
/ Cost control
/ Genetic algorithms
/ Humanities and Social Sciences
/ Linear matrix inequality
/ multidisciplinary
/ Neural networks
/ Robust-optimal control
/ Rotary inverted pendulum
/ Science
/ Science (multidisciplinary)
/ Simulation
/ Stability control
/ Systems stability
/ T–S fuzzy descriptor model
2024
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Robust-optimal control of rotary inverted pendulum control through fuzzy descriptor-based techniques
by
Bui, Ngoc-Tam
, Pham, Duc-Binh
, Dao, Quy-Thinh
, Nguyen, Thi-Van-Anh
in
639/166
/ 639/166/988
/ Adaptability
/ Controllers
/ Cost control
/ Genetic algorithms
/ Humanities and Social Sciences
/ Linear matrix inequality
/ multidisciplinary
/ Neural networks
/ Robust-optimal control
/ Rotary inverted pendulum
/ Science
/ Science (multidisciplinary)
/ Simulation
/ Stability control
/ Systems stability
/ T–S fuzzy descriptor model
2024
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Robust-optimal control of rotary inverted pendulum control through fuzzy descriptor-based techniques
by
Bui, Ngoc-Tam
, Pham, Duc-Binh
, Dao, Quy-Thinh
, Nguyen, Thi-Van-Anh
in
639/166
/ 639/166/988
/ Adaptability
/ Controllers
/ Cost control
/ Genetic algorithms
/ Humanities and Social Sciences
/ Linear matrix inequality
/ multidisciplinary
/ Neural networks
/ Robust-optimal control
/ Rotary inverted pendulum
/ Science
/ Science (multidisciplinary)
/ Simulation
/ Stability control
/ Systems stability
/ T–S fuzzy descriptor model
2024
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Robust-optimal control of rotary inverted pendulum control through fuzzy descriptor-based techniques
Journal Article
Robust-optimal control of rotary inverted pendulum control through fuzzy descriptor-based techniques
2024
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Overview
Expanding upon the well-established Takagi–Sugeno (T–S) fuzzy model, the T–S fuzzy descriptor model emerges as a robust and flexible framework. This article introduces the development of optimal and robust-optimal controllers grounded in the principles of stability control and fuzzy descriptor systems. By transforming complicated inequalities into linear matrix inequalities (LMI), we establish the essential conditions for controller construction, as delineated in theorems. To substantiate the utility of these controllers, we employ the rotary inverted pendulum as a testbed. Through diverse simulation scenarios, these controllers, rooted in fuzzy descriptor systems, demonstrate their practicality and effectiveness in ensuring the stable control of inverted pendulum systems, even in the presence of uncertainties within the model. This study highlights the adaptability and robustness of fuzzy descriptor-based controllers, paving the way for advanced control strategies in complex and uncertain environments.
Publisher
Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
Subject
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