Information technology for automation of fuzzy control with non-linear constraints
DOI №______
Abstract
Existing information technologies of fuzzy control are based on fuzzy logic that uses the membership function of one argument and considers the control problem without constraints, covering several control variables. Fuzzy control of complex systems with the presence of non-linear constraints on control variables can be realized based on the use of fuzzy logic with the membership function of several arguments. The article proposes a method for constructing information technologies for solving problems of fuzzy control of complex systems with non-linear constraints. The concept of the infologic modeling of the problem of fuzzy control with constraints is proposed, the mathematical formulation of the problem is formalized and the stages of conducting fuzzy inference for solving it are developed. The concept of infologic modeling of the subject area of the problem of fuzzy control with constraints involves the construction of a conceptual model of the problem of fuzzy control, a model of linguistic variables, a model of the structure of fuzzy inference rules. On the basis of the conceptual model, the mathematical formulation of the management problem is formalized in the form of a set of fuzzy product rules and a system of fuzzy nonlinear constraints represented by the membership function of several arguments. The procedure of fuzzy inference is proposed, which contains the stages of fuzzification, aggregation, activation, accumulation and defuzzification. At the accumulation stage, non-linear constraints are taken into account. In case of defuzzification, the required values of control variables of information technology are calculated. The results of the work can be used to develop information technologies that automate the management of systems with constraints on the values of control variables.
Keywords: complex system, fuzzy control, non-linear constraints, information technology, membership function of several arguments
References (MLA)
1. Mamdani E. H., and Assilian S. "An Experiment in Linguistic Yn Thesis With A Fuzzy Logic Controller." International Journal of Man-Machine Studies 7(1) (1975): 1-13. Print.
2. Zadeh L. A. "Fuzzy Sets." Information and Control 8 (1965): 338-353. Print.
3. Hostev V. I. Designing Fuzzy Controls for Automatic Control Systems. Nizhyn: Aspekt-Polihraf, 2009. Print.
4. Leonenkov A. V. Fuzzy Modeling in the Environment of MATLAB and FuzzyTECH. Sankt-Peterburg: BKhV- Peterburh, 2005. Print.
5. Rotshtein A. P. Intellectual Identification Technologies: Fuzzy Logic, Genetic Algorithms, Neural Networks. Vinnytsia: Universum-Vinnytsia, 1999. Print.
6. Shushura A. N., and Tarasova I. A. "A Method of Fuzzy Control Based on Variables with Multidimensional Membership Functions." Shtuchnyi intelekt 1 (2010): 122-128. Print.