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Keyword: dynamic model

  • Implementation of INS for control of robots with a DC motor

    • Boţek P.
    • Mudrikova A.
    Industry 4.0, Vol. 4 (2019), Issue 3, pg(s) 116-119
    • Abstract
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    This paper describes the activity system and the importance of INS with the possibility of implementation to the robot control. The contribution also introduces the execution of DC motor regulation utilized for the positioning of a rotary positioned arm. The motor control comprises the current regulation, angular velocity and the rotation of the motor shaft fixed to the arm regarding the required angular change course of the arm rotation. The regulation structure of the DC motor is carried out in MATLAB/Simulink program. The arm movement is investigated via the mathematical model and virtual dynamic model formed in MSC.ADAMS program.

  • RESEARCH ON DYNAMIC TURNING PROCESS OF TRACTORS TRAILERS AGGREGATE WITH MOUNTED DAMPERS AGAINST SUDDEN BENDING

    • Zung V. Z.
    Machines. Technologies. Materials., Vol. 8 (2014), Issue 8, pg(s) 17-20
    • Abstract
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    This paper introduces cycle dynamic model of combined tractors – trailer with mounted damper against sudden bend in order to increase stability when turning round. The research results can make rational basis for selection of appropriate parameters of the damper.

  • A STUDY ON THE IMPLEMENTATION OF THE DISCIPLINED CONVEX OPTIMIZATION METHOD FOR THE IDENTIFICATION OF THE DYNAMIC SYSTEMS’ MODELS

    • Danila A.
    Innovations, Vol. 3 (2015), Issue 2, pg(s) 28-31
    • Abstract
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    In this paper the author investigated the implementation of the convex optimization method in the area of the estimation of model parameters from experimental data. The investigation focused on the identification of processes within the technical environment such as: the liquid flow process, the mechanical vibrating process and the electric arc discharge. The theoretical support related to the convex optimization algorithm is emphasized in the first section of the paper. The preconditions for the implementation of the algorithm within the system identification context are also presented. In the third and the fourth sections, the main analysis is made. The mathematical models of the processes under investigation and the software implementations are depicted. The results showed that for an input signal, equivalent with the Dirac impulse, the disciplined convex optimization algorithm provide consisted estimate of the process under investigation which is similar to the results from the classical least-squares identification algorithm. These results are the basis for further investigations on the implementation of the convex optimization algorithm for system identification.

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