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Modern living conditions and growing uncertainties in the decision in choosing strategy conduct for transport enterprises, define the trend to create automatic systems of decision-making and forecasting. The fundamental and powerful argument for the creation of fuzzy logic systems is the reduction of costs (resource consumption) now as a result of economic and technological activities. Rational use of resources now depends on the basic performance management system. The proposed methods of information processing in the existing algorithms cannot solve this problem in its entirety, so synthesis proposed new algorithms and approaches that are used to build neural networks, with the possibility of learning. In this article we consider the problem of synthesis of nonlinear algorithms for multi-mode process control (transport company) in the state space. A new algorithmic approach to the synthesis of the non-linear multi-mode controller for TP (transport companies), the disclosure of which is given in the form of a set of linear models is presented. At the executive management level to ensure solved the problem of maintaining high-precision settings to (dynamically changing object) with given constraints on the dynamic characteristics of the system. For example, TP, these restrictions are related to ensuring high reliability of functioning of the ACS (automatic control system). Design decisions at the executive level of the synthesis process control algorithms are implemented on the basis of algorithms that satisfy the principle of minimal complexity. A characteristic feature of the search task of project solutions at the executive level is the need to take account of the nonlinear nature of the work of TP in different modes of operation, which significantly complicates the problem of defining the optimal solution.

SYNTHESIS OF NONLINEAR ALGORITHMS FOR MULTIMODE CONTROL OF TRANSPORT ENTERPRISES IN AN INDETERMINATE STATE