Synthesis of a quasi-optimal fuzzy controller model under a priori uncertainty in intelligent transport underactuated systems

Abstract

The research paper presents the synthesis of a fuzzy quasi-optimal controller model and an analysis of its effectiveness compared to a known train speed controller for short-term deviations from the specified operating mode. The task of controlling an underactuated system is of particular importance for railway transport, especially for high-speed transportation. Mechanical systems as control objects are essentially nonlinear dynamical systems of high order. In addition, the complexity of optimizing the operating modes of such systems is due to the fact that even detailed modeling does not accurately predict the cumulative effect of all dynamic factors acting on a dynamic system under operating conditions. Traditionally used in practice linear control laws with constant coefficients are designed to stabilize only one specific mode of motion, which makes them ineffective in conditions of control deficit and a priori uncertainty. Using the reduction of the Lagrange optimization problem to the isoperimetric one makes it possible to obtain a quasi-optimal solution to the structural synthesis problem, which increases control efficiency compared to known methods. The use of the fuzzy logic apparatus allows for parametric synthesis of control, providing adaptability to a priori uncertain operating conditions.