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Advanced Optimal Control Problem and Numerical Method for its Solving

https://doi.org/10.17587/mau.25.111-120

Abstract

The advanced statement of the optimal control problem is presented. The difference between the extended setting of the problem and the classical one is that the model of the control object consists of two subsystems, a reference model, which generates an optimal motion path and a dynamic model of the control object with a system for stabilizing movement along the optimal trajectory. In the problem, it is necessary to find a program control function whose argument is time and a stabilization system function whose argument is the deviation of the state vector of the control object from the optimal program trajectory. The task has many initial conditions, one of which is used in the search for software control, and the rest for the search for a stabilization system. The control quality criterion is defined as the sum of the original quality criterion for all specified initial conditions. The procedure for trans forming the classical setting of the optimal control problem to an extended setting based on the refinement of the problem for its practical implementation is presented. To solve the extended optimal control problem, a universal numerical method is proposed based on a piecemeal linear approximation of the control function using evolutionary algorithms and symbol regression methods for structurally parametric optimization of the stabilization system function. An example of solving an extended optimal control problem for spatial motion by a quadcopter, which should conduct reconnaissance of a given territory in a minimum time, is given.

About the Author

A. I. Diveev
Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences, FRC CS RAS
Russian Federation

Dr. Sc., Professor, Chief Researcher

Moscow



References

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Review

For citations:


Diveev A.I. Advanced Optimal Control Problem and Numerical Method for its Solving. Mekhatronika, Avtomatizatsiya, Upravlenie. 2024;25(3):111-120. (In Russ.) https://doi.org/10.17587/mau.25.111-120

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