Synthesis of an intelligent law of electric locomotive control based on the reduction of the Lagrange problem to an isoperimetric problem
https://doi.org/10.46973/0201-727X_2024_3_119
Abstract
The process of functioning of an intelligent information and control system is represented by a semantic network of typical situations, each of which can be described by a semantic network of problem subsituations with corresponding optimization tasks. When the dynamics of the ongoing processes satisfies the Hamilton-Ostrogradsky principle, the synthesis of controls on the basis of the reduction of the Lagrange problem to an isoperimetric problem leads to a two-point boundary value problem, from which follows a set of quasi-optimal control structures. They can form the basis for the construction of a rule base. In this re-search paper, one of the variants of the control law is synthesized, where fuzzy logic is used to eliminate the uncertainty of the choice of its parameter according to the problem substitution. The constructiveness of the synthesized intelligent control law is demonstrated by the example of solving the problem of stabilizing the speed of a train with a single electric locomotive.
About the Author
S. V. Lazarenko
Rostov State Transport University (RSTU)
Russian Federation
Russian Federation
Lazarenko Sergey Valeryevich, Chair «Communication on Railway Transport», Candidate of Engineering Sciences, Associate Professor
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Review
For citations:
Lazarenko S.V. Synthesis of an intelligent law of electric locomotive control based on the reduction of the Lagrange problem to an isoperimetric problem. Vestnik Rostovskogo Gosudarstvennogo Universiteta Putej Soobshcheniya. 2024;(3):119–129. (In Russ.) https://doi.org/10.46973/0201-727X_2024_3_119
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