Abstract
The paper presents the simulation of an intelligent DC electric drive control system (SUEP) with two-zone speed control using the fuzzy sets theory. A developed fuzzy SUEP with two-zone speed control has been implemented. The results comparative analysis of modeling an intelligent control system and an electric drive system using classical approaches to adjusting regulators is presented, and the advantages and disadvantages of using soft computing in an intelligent control system for an AC electric drive are revealed. The dynamic characteristics of classical and intelligent control systems are investigated. The introduction of a multi-cascade fuzzy controller into intelligent control systems, where the external cascade of the fuzzy module is considered as an expert system that controls the nested cascade controllers, allows reducing the information load of the production knowledge base, the number of linguistic variables, and also reducing the algorithmic complexity in the fuzzification and defuzzification blocks. Algorithms and procedures used in multistage fuzzy controllers can be used as prediction modules in advanced automation objects, for example, in electric drive control systems with two-zone regulation, as well as similar technological processes used in the electric power industry, robotics and transport. This approach allows a fuzzy multi-stage control system to combine various structural solutions for setting up controllers, while obtaining qualitative characteristics of transient processes, and to expand the intellectual capabilities of fuzzy control systems by combining them structurally and functionally into multi-stage structures to solve the problems of regulating complex technological processes under condition -views of multi-criteria, multi-tasking and multi-coordinate.
Keywords
electric drive control system, two-zone regulation, fuzzy inference algorithms, fuzzy logic controller
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