ANALYTICAL MODELING EVALUATION AND MANAGEMENT OF OPERATIONAL STATE OF POWERFUL DRUM MILLS AS INTELLIGENT AGENTS
DOI:
https://doi.org/10.32782/IT/2022-2-6Keywords:
multi-agent systems, intellectual agents, drum mill, dynamic programming, state variables, optimization of evaluation and managementAbstract
The use of intelligent multi-agent systems in the technological processes of mining and processing enterprises, taking into account the complexity and power of the units used here, requires research and analytical justification for the functioning of assessment and management systems in this environment. A promising approach is the ability to present each technological unit, namely a powerful drum mill with a control system, as an intelligent agent in the whole set of technological and technical processes actually existing here. The aim of the work is to study the possibility of analytical modeling of evaluation and management of the operational state of powerful drum mills as intelligent agents using an observer. The methodology for ensuring the solution of the presented problem is to apply the reflection of the operational state of a powerful drum mill through the internal state of the agent in state variables, which to minimizes the resources for the formation of initial assessment and control solutions. The scientific novelty is in the application of analytical modeling in state variables, using the principle of dynamic programming by R. Bellman to present the internal technical and technological state of the drum mill through the state of the agent, using a discrete observer for operational evaluation and control. This allows optimization according to a given criterion for the accuracy and energy consumption of the initial solutions that are formed in the system. Conclusions. The justified application of equations in state variables written in the normal Koshi form to represent the internal state of the agent of a powerful drum mill presents an opportunity to more effectively work out the formation of optimal laws of decisions made according to a given criterion for accuracy and energy consumption.
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