Control Structures Based on Fuzzy Logic

Dear Colleagues

This Special Issue in the open-access journal Computers (ISSN 2073-431X) wants to promote new research results in the field of advanced control structures based on fuzzy logic. Fuzzy logic is an important concept in the theory of intelligent control systems. Based on this, new methods in the control domain and decision-making have been developed. The first applications in the field of regulation began in 1975. Since 1985, especially in Japan, a real explosion of practical applications has occurred using fuzzy logic. In the literature, numerous research results have been reported for the use of fuzzy logic principles in the control of industrial processes. Fuzzy logic offers a different way of dealing with control problems, compared to classical methods based on linear PID controllers. In the case of fuzzy regulation, conventional algorithms are replaced by a series of linguistic rules of the if (condition) then (conclusion). This gives a heuristic algorithm, and can take into account the operator's experience in controlling the process. The Issue aims to include new research results in scientific fields such as fuzzy controllers for linear and non-linear systems, advanced fuzzy logic control structures, fuzzy algorithms for search, classification, approximation and learning, technology, implementation, and practical applications. The authors are invited to publish working examples and case studies resulting from their research in the field, presenting precise methods of designing fuzzy logic-based regulation systems; precise methods of stability analysis; the possibility of using fuzzy logic for conducting complex, non-linear, and time-varying processes using process linguistic knowledge, deduced from expert knowledge on control issues; and the possibility of performing exceptional treatments, with changing control strategies as a result of a change in the process, to demonstrate the confidence in these structures and that they can undoubtedly provide a better quality of control. Readers are eager to receive new solutions and answers to questions related to emerging theoretical fuzzy logic control structure applications and their implementation.

Topics:

Fuzzy mathematics to develop fuzzy controllers;
Fuzzy modeling;
Takagi–Sugeno structures;
Fuzzy PID controllers;
Fuzzy controllers for non-linear MIMO systems;
Model predictive fuzzy control;
Adaptive fuzzy logic control;
Self-tuning fuzzy logic control;
Optimization-based fuzzy control;
Fuzzy algorithms for search, classification, approximation, and learning;
Bi-fuzzy and fuzzy random in optimization systems;
Type 2 fuzzy controllers;
Intelligent control;
Fuzzy expert systems;
Dynamic neuro-fuzzy structures;
Genetic fuzzy logic structures;
Technologies and applications;
Implementation of fuzzy control structures in fuzzy control languages and practical software as Simulink or LabView;
Industrial application of fuzzy control.

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