Abstract
This paper presents a digital twin of a mechatronic drive based on a brushless DC (BLDC) motor model based on a nonlinear discrete optimal control model. Some parameters of a BLDC motor, such as resistance and inductance of windings, magnetic flux, viscous friction coefficient in bearings, angular velocity and electromagnetic moment, can change due to both degradation of structural elements and external forces. Simulation by a complete enumeration of the values of the parameters of the mechatronic device with a certain step will make it possible to adapt the program of the control device to changing operating conditions according to the criterion of minimizing the control energy by changing the parameters of the state matrices and control of the digital twin. As a result, the accuracy of the movement of the mechatronic device along the given trajectory will increase due to the greater correspondence of the control parameters to the real object.
Highlights
In connection with the development in industry of complex and capital-intensive production systems, accidents on which can lead to significant losses due to expensive repairs, and the significant development of data transmission facilities, computer technology and storage devices for large amounts of data, the concept of digital twins has appeared. [15]
Methods and mathematical models for such forecasting, based on the methods of mathematical statistics, were widely developed in the 20th century. This approach, based on recording a large amount of measurement data in the database, makes it possible to form training samples of conditionally "suitable", that is, those capable of fulfilling a functional purpose with a high probability, and conditionally "unusable elements of systems that can lead to an accident. the entire system soon and must be replaced immediately. Another approach involves modeling the parameters of the control algorithm in order to adapt it to changing operating conditions both due to material degradation and environmental changes
This paper presents a mathematical model of a digital twin for a brushless DC (BLDC) motor, as an element of a production line, and optimally controlled using a nonlinear algorithm
Summary
In connection with the development in industry of complex and capital-intensive production systems, accidents on which can lead to significant losses due to expensive repairs, and the significant development of data transmission facilities, computer technology and storage devices for large amounts of data, the concept of digital twins has appeared. [15]. Methods and mathematical models for such forecasting, based on the methods of mathematical statistics, were widely developed in the 20th century This approach, based on recording a large amount of measurement data in the database, makes it possible to form training samples of conditionally "suitable", that is, those capable of fulfilling a functional purpose with a high probability, and conditionally "unusable elements of systems that can lead to an accident. Modeling the operating conditions from the model will allow the controller to adapt to changing operating conditions
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