A Comprehensive Survey on Advanced Control Techniques for T-S Fuzzy Systems Subject to Control Input and System Output Requirements

This paper provides a comprehensive survey on advanced control techniques for Takagi-Sugeno (T-S) fuzzy systems that are subject to input and output performance constraints. The focus is on addressing practical applications, such as actuator saturation and output limits, which are often encountered...

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Vydáno v:Processes Ročník 13; číslo 3; s. 792
Hlavní autoři: Chang, Wen-Jer, Lin, Yann-Horng, Ku, Cheung-Chieh
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 09.03.2025
Témata:
Actuators
Adaptive control
Antiwindup compensators
Constraints
Control engineering
Control equipment
Control methods
Control systems
Controllers
Disturbances
Engineering
Fault diagnosis
Feedback
Fuzzy algorithms
Fuzzy control
Fuzzy logic
Fuzzy sets
Fuzzy systems
Linear matrix inequalities
Methods
Nonlinear control
Nonlinear systems
Optimization techniques
Predictive control
Real time
Robotics
Robust control
Surveys
Systems stability
Timing
ISSN:2227-9717, 2227-9717
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Shrnutí:This paper provides a comprehensive survey on advanced control techniques for Takagi-Sugeno (T-S) fuzzy systems that are subject to input and output performance constraints. The focus is on addressing practical applications, such as actuator saturation and output limits, which are often encountered in industries like aerospace, automotive, and robotics. The paper discusses key control methods such as model predictive control, anti-windup compensators, and Linear Matrix Inequality (LMI)-based control, emphasizing their effectiveness in handling input and output constraints. These techniques ensure system stability, robustness, and performance even under strict physical limitations. The survey also highlights the importance of T-S fuzzy systems, which provide a flexible framework for modeling and controlling nonlinear systems by breaking them down into simpler linear models. Additionally, recent developments in robust and adaptive control strategies are explored, particularly in handling time delays, disturbances, and uncertainties. These methods are crucial for real-time applications where the system must remain stable and safe despite unmeasured states or external disturbances. By reviewing these advanced techniques, the paper aims to identify research gaps and future directions, particularly in scalable solutions and integrating data-driven approaches with T-S fuzzy control frameworks.
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ISSN:2227-9717
2227-9717
DOI:10.3390/pr13030792