An approach to constructing an intellectual distributed decision support system when managing a group of self-controlling robotic agents under the conditions of distabilizing physicians

This paper proposes a promising approach to the construction of an intelligent distributed decision support system (IDSSP) when controlling a group of self-controlled robotic means operating under the influence of destabilizing factors.

Purpose is to improve the efficiency and survivability of self-controlled robotic means functioning as part of a group in the event of destabilizing factors.

An architecture for constructing an IRSSPR is presented that allows to expand the possibilities of solving target problems of selfcontrolled robotic means, taking into account the replenishment of databases and knowledge bases using a neural network unit and to provide decision support in conditions of multi-model distributed computing elements of the system. An algorithm for the optimal solution of the problem of simultaneous multitasking arising when controlling a group of self-controlled robotic means is proposed. The idea of creating an IDSSPR based on the complex use of mathematical methods (neural networks and fuzzy logic) to increase the reliability of the results obtained and reduce the time for solving problems when controlling a group of self-controlled robotic means is proposed. The possibility of implementing the proposed system in the design of on-board control systems for new samples of selfcontrolled robotic means, based on the recommendations issued by the system (optimal solution), is not excluded, which will make it possible to reconfigure the control algorithms based on the current situation.