Learning Fuzzy Control of Nonlinear Processes

摘要

Due to high nonlinearities and time-varying dynamics of today's control systems fuzzy learning controllers find appliance in practice. The present paper proposes a method for the synthesis of the learning fuzzy controllers where an expert knowledge about a process is applied to form a learning mechanism that is used to acquire information for the knowledge base of the main fuzzy controller. According to the proposed method an expert knowledge is used to describe how the controller should learn to control rather than to control the process. The results of experiments on heating system and level/pressure system prove the practical relevance of the design strategy of a learning fuzzy controller.%Straipsnyje nagrinėjamas netiesinio objekto valdymas neraiškios logikos reguliatoriais. Pasiūlyta bendra mokslaus neraiškia logika pagrįsto reguliatoriaus struktūra, kur eksperto patirtis ir žinios panaudojamos reguliatoriaus mokymo algoritmų sudarymui, o ne valdymo taisyklių formulavimui, ir parodytas tokio reguliatoriaus pritaikymas dviejuose netiesinio valdymo uždaviniuose: vandens lygio ir oro slėgio valdyme, bei šildymo sistemos valdyme. Eksperimentiškai parodytas ir palygintas su kitais reguliatoriais pasiūlytos struktūros reguliatorių pakankamas efektyvumas.