Fuzzy System Identification and Adaptive Control

This comprehensive guide on adaptive control and identification of Takagi–Sugeno fuzzy systems offers valuable insights for engineers and researchers alike.

This book provides readers with a systematic and unified framework for the identification and adaptive control of Takagi–Sugeno (T–S) fuzzy systems. The authors delve into a comprehensive study of fuzzy system identification and control challenges, utilizing T–S fuzzy system tools for function approximation and feedback control of nonlinear systems. By integrating theory with practical applications, this work serves as a valuable resource for those looking to navigate the complexities of fuzzy logic in control systems.

In Fuzzy System Identification and Adaptive Control, readers will find design techniques that empower them to apply these robust tools to tackle intricate nonlinear control problems effectively. The book covers essential concepts of fuzzy sets, logic, and inference systems, providing a solid foundation for understanding T–S fuzzy systems. Additionally, it explores offline and online identification algorithms, various controller structures, and adaptive control strategies tailored for continuous and discrete-time T–S fuzzy systems.

Furthermore, the authors address adaptive fault compensation issues for T–S fuzzy systems affected by actuator faults, expanding the scope of the discussion to include a wide range of related technical topics. This comprehensive approach equips engineers in mechanical, electrical, and aerospace fields with the tools needed to solve complex control design problems. Fuzzy System Identification and Adaptive Control also serves as a reference for researchers and academics focused on nonlinear, intelligent, adaptive, and fault-tolerant control methodologies.