Comparing Fuzzy logic with classical controller designs
IEEE Transactions on Systems, Man and Cybernetics
Fuzzy control theory: a nonlinear case
Automatica (Journal of IFAC)
Pad-analysis of fuzzy control stability
Fuzzy Sets and Systems
Fuzzy control rules and their natural laws
Fuzzy Sets and Systems
Theory of the fuzzy controller
Fuzzy Sets and Systems
Fuzzy controllers: lifting the linear-nonlinear frontier
Fuzzy Sets and Systems
Studies on the output of fuzzy controller with multiple inputs
Fuzzy Sets and Systems
Essentials of fuzzy modeling and control
Essentials of fuzzy modeling and control
Explicit formulas for fuzzy controller
Fuzzy Sets and Systems
Towards a paradigm for fuzzy logic control
Automatica (Journal of IFAC)
An approach to fuzzy control of nonlinear systems: stability and design issues
IEEE Transactions on Fuzzy Systems
New design and stability analysis of fuzzy proportional-derivative control systems
IEEE Transactions on Fuzzy Systems
Typical Takagi--Sugeno PI and PD fuzzy controllers: analytical structures and stability analysis
Information Sciences—Informatics and Computer Science: An International Journal
Research on decision tree induction from self-map space based on web
Knowledge-Based Systems
Design of hierarchical fuzzy PID controller based on granular computing in LabVIEW
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 4
Concept of analog flexible fuzzy control and its application in control system of power plant
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 6
New delay-dependent stability criteria for T--S fuzzy systems with time-varying delay
Fuzzy Sets and Systems
Robust Fuzzy Control of Electrical Manipulators
Journal of Intelligent and Robotic Systems
Hi-index | 22.15 |
Takagi-Sugeno (TS, for short) fuzzy controllers have been used and treated as black-box controllers, and there exists no explicit structure of any TS fuzzy controller in the literature. In this paper, we investigate the analytical structure of the TS fuzzy controllers that use our newly introduced simplified TS control rule scheme. Our scheme requires that all the rule consequent employ a common linear function and be proportional to one another. The scheme drastically reduces the number of adjustable parameters required by the original TS rule scheme. Product fuzzy logic AND was employed in the rule antecedents. We theoretically proved that the TS controllers using the simplified rule scheme were nonlinear variable gain controllers. The proportionality of the rule consequent parameterized the gain variation characteristics. As special cases, the TS controllers with three or two input variables and the simplified linear rule consequent were nonlinear variable gain PID, PI or PD controllers. As an illustration, we mathematically analyzed the nonlinear variable gain PI controllers, and revealed that the gain variation empowered the controllers to outperform their linear counterparts. Stability of the nonlinear PI control systems was also addressed. A practical example is given to show how to achieve the desired characteristics of the gain variation by properly designing the simplified rules.