4.7 Article

Fundamentals of Synthesized Optimal Control

Journal

MATHEMATICS
Volume 9, Issue 1, Pages -

Publisher

MDPI
DOI: 10.3390/math9010021

Keywords

optimal control; Lyapunov stability; equilibrium point; symbolic regression; Pontryagin's maximum principle

Categories

Funding

  1. Ministry of Science and Higher Education of the Russian Federation [075-15-2020-799]

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This paper presents a new formulation of the optimal control problem with uncertainty, introducing the concept of feasibility of the mathematical model of the object. It shows that this feasibility property is crucial for the development of stable practical systems. The method proposed in the article aims to ensure system feasibility and stability, and is insensitive to uncertainties in the mathematical model of the object.
This paper presents a new formulation of the optimal control problem with uncertainty, in which an additive bounded function is considered as uncertainty. The purpose of the control is to ensure the achievement of terminal conditions with the optimal value of the quality functional, while the uncertainty has a limited impact on the change in the value of the functional. The article introduces the concept of feasibility of the mathematical model of the object, which is associated with the contraction property of mappings if we consider the model of the object as a one-parameter mapping. It is shown that this property is sufficient for the development of stable practical systems. To find a solution to the stated problem, which would ensure the feasibility of the system, the synthesized optimal control method is proposed. This article formulates the theoretical foundations of the synthesized optimal control. The method consists in making the control object stable relative to some point in the state space and to control the object by changing the position of the equilibrium points. The article provides evidence that this approach is insensitive to the uncertainties of the mathematical model of the object. An example of the application of the method for optimal control of a group of robots is given. A comparison of the synthesized optimal control method with the direct method on the model without disturbances and with them is presented.

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