The article deals with the issues of intelligent, based on genetic algorithms, systems for grinding of grainy biomass to be used for further energy production processes. The aim of the study is to develop the basis for processing, active monitoring and subsequently, adaptive control of the process functional characteristics on the basis of solutions provided by artificial intelligence and identification of input variables of mathematical models and indexes, their mutual relations as well as

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... r impact on the output variables such as: degree of fineness, production yield, power demand and unit energy consumption as well as CO 2 emissions. A research methodology for practical control of the grinding potentials to improve the parameters of the multi disc grinding process parameters including: energy and power consumption, the product granulometry and the process efficiency improvement; CO 2 emission index being a determinant of environmental efficiency has been developed. Parameters providing the grinding process with best possible conditions in terms of energy efficiency and emissivity, depending on the kind of the feed material, have been determined