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The synthesis of fuzzy controllers on the base MATLAB


G. N. Arsen’ev, A. A. Shalygin

The aim is to develop a methodology of designing fuzzy controllers (FC) based on fuzzy inference Mamdani using the Max-Min Inference method in logical solutions [12,13]. Different versions of the synthesis of fuzzy controllers with identical input and output triangular membership functions PT formulated methods of parametric synthesis of digital fuzzy controllers in a closed system of automatic control, which uses an interactive system MATLAB. The principle of fuzzy controllers most often based on the use of the algorithm «Minimax» fuzzy Mamdani (Max-Min Inference). In addition, the most-more often used the same triangular membership functions for input parameters, and for the output parameter of a fuzzy controller. In the synthesis of fuzzy controllers to use triangular membership functions instead of exponential, Gaussian, Z-and S-functions can often get better quality systems, automatic control. In this paper we formulated the method of parametric synthesis of digital fuzzy controllers, HP closed automatic control systems. This technique consists in the following steps. 1) as input variables using the HP error, the first derivative and second derivative of the error. Output variable – control action on the object of control. 2) to choose the type of membership functions of AF fuzzy terms, evaluating the input and output variables are HP's universal set [0,1]. Number of terms for each variable is chosen to be equal to two, such as an error – negative, positive. In this case, the PT – the universal set of continuous, symmetric (one decreases the other increases), intersecting at a value of ABS-tsissy 0,5. 3) form the two (the number of terms) of linguistic control rules and carries out the formalization of linguistic rules man-agement system of logic equations. 4) specifies the initial values of parameters to be optimized HP – ranges of change of the input and output variables and parameters of HP PT. 5) defines the quantization step in the system, the observation time interval, select a criterion for the quality and method of parametric optimization. 6) step forward with the simulation () crite-rion of quality closed-loop system under the given set value and injurious action is chosen for the observation interval. 7) repeat the procedure (with a different ranges of input and output variables and parameters of the FP) until such time as there is no on-lucheno a minimum quality criterion or satisfies the developer's quality management system with FC. Different membership functions and algorithms Mamdani and Sugeno fuzzy you-water laid in a package of fuzzy logic (Fuzzy Logic Toolbox) interactive system MATLAB, but you can not use the online system MATLAB to calculate the non-precise controls, and carry out the calculation with the help of a computer by a specially composed programs.
June 24, 2020
May 29, 2020

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