Abstract
This paper presents the synthesis of a controller for robot arm servo drive by placing the poles of the transfer function. The problem of synthesis is determined, based on the desired duration of the transition process, the desired location of the roots of the characteristic equation of closed system and space state variables regulator factors are found that provide the desired system performance. There was used Ackerman’s formula for the synthesis of regulator that allows for the placement of all poles of the transfer function of a closed system at given points of the plane of the roots of the characteristic equation. Synthesis by placing poles is based on the use of model automatic control system state variables in space. As well as there is synthesized block diagram of the controller for robot arm servo drive and both held it modeling in MATLAB and moved it in Simulink environment. Due to the stated values of transition time and output signal displacement that provide the allowed divergence between output signal and sample, proposed control system works in automatic mode.
Highlights
INTRODUCTIONThe task of creating any system of automatic control is to complement the controlled object with such external links that ensure the passage of processes in an object in accordance with certain preformulated criteria
The task of creating any system of automatic control is to complement the controlled object with such external links that ensure the passage of processes in an object in accordance with certain preformulated criteria.The choice of these criteria is determined by the fact that the purpose of the functioning of the automatic control system is to provide at any time at the output of the controlled object such regulated value that is the closest to the given one
This method is based on using artificial neural network [8,9,10,11,12,13,14,15,16] as a universal approximating device, which in the process of training based on defined sequences, can accommodate to the input data in order to get at the output of the network the values as close as possible to the related output signals given in the form of the objective function
Summary
The task of creating any system of automatic control is to complement the controlled object with such external links that ensure the passage of processes in an object in accordance with certain preformulated criteria. Concerning the nonlinear dynamical systems, it is difficult to construct an analytical model in this case, so it is expedient to use a method that provides the capability of automatically building up the necessary models This method is based on using artificial neural network [8,9,10,11,12,13,14,15,16] as a universal approximating device, which in the process of training based on defined sequences, can accommodate to the input data in order to get at the output of the network the values as close as possible to the related output signals given in the form of the objective function
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.