Abstract
Frequently the reliabilities of the linguistic values of the variables in the rule base are becoming important in the modeling of fuzzy systems. Taking into consideration the reliability degree of the fuzzy values of variables of the rules the design of inference mechanism acquires importance. For this purpose, Z number based fuzzy rules that include constraint and reliability degrees of information are constructed. Fuzzy rule interpolation is presented for designing of an inference engine of fuzzy rule-based system. The mathematical background of the fuzzy inference system based on interpolative mechanism is developed. Based on interpolative inference process Z number based fuzzy controller for control of dynamic plant has been designed. The transient response characteristic of designed controller is compared with the transient response characteristic of the conventional fuzzy controller. The obtained comparative results demonstrate the suitability of designed system in control of dynamic plants.
Highlights
In industry some dynamic plants are characterized by uncertainty of environment and fuzziness of information
The analyses have shown that the control of dynamic plants is basically implemented using input variables error and change-in-error
The paper presents the design of Z number based fuzzy inference system
Summary
In industry some dynamic plants are characterized by uncertainty of environment and fuzziness of information. Taking into consideration the reliability degree of fuzzy values used in the fuzzy If- rules the design of decision-making module acquires importance. Advances in Fuzzy Systems fuzzy set with a footprint of uncertainty and by computing the centroid it is converted to the crisp numbers for decision-making. These researchers present the advantages of the presented approach based on their low computational complexity. The derivation of the interpolative approximate reasoning for Z number based fuzzy rules is considered.
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