Fuzzy control theory: a nonlinear case
Automatica (Journal of IFAC)
Fuzzy control rules and their natural laws
Fuzzy Sets and Systems
Analytic formulation of linguistic rules for fuzzy controller
Fuzzy Sets and Systems
An introduction to fuzzy control (2nd ed.)
An introduction to fuzzy control (2nd ed.)
Fuzzy PID controller: Design, performance evaluation, and stability analysis
Information Sciences: an International Journal - Special issue analytical theory of fuzzy control with applications
Analysis of direct action fuzzy PID controller structures
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Flexible complexity reduced PID-like fuzzy controllers
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Two-level tuning of fuzzy PID controllers
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Theoretical and linguistic aspects of the fuzzy logic controller
Automatica (Journal of IFAC)
Decomposition property of fuzzy systems and its applications
IEEE Transactions on Fuzzy Systems
A systematic study of fuzzy PID controllers-function-based evaluation approach
IEEE Transactions on Fuzzy Systems
Fuzzy controllers: synthesis and equivalences
IEEE Transactions on Fuzzy Systems
Fuzzy basis functions, universal approximation, and orthogonal least-squares learning
IEEE Transactions on Neural Networks
Design of fuzzy PID controllers using modified triangular membership functions
Information Sciences: an International Journal
Fuzzy controller design for temperatures of continuous soaking process in sugar plant
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 4
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This paper proposes a novel algorithm to produce an analytical solution for three-input fuzzy PID systems. The analysis is based on the most common inference method, Zadeh-Mamdani's min-max-gravity fuzzy reasoning. Two types of fuzzy systems are investigated. Both types use unevenly distributed triangular shaped fuzzy input memberships. In the first type, the output fuzzy sets are considered to be uniformly distributed symmetrical triangular type memberships and in the second type the output fuzzy sets are considered unevenly distributed singleton functions. A new input transformation technique is developed to reduce the number of input conditions required in defining the fuzzy output. The multi-phase complexity that exists in conventional fuzzy reasoning analysis is thus avoided. An efficient solution algorithm is outlined to produce the general fuzzy output solution using a minimum number of nonlinear expressions. With the proposed method, the fuzzy output solution for a three-input fuzzy system having uniform output membership functions requires only two nonlinear expressions. When the output fuzzy sets are unevenly distributed, the general three-input based solution requires only four nonlinear expressions. The fuzzy controller output is finally decomposed into linear and nonlinear parts. The output decomposition is useful in defining tuning gains for fuzzy PID systems.