Abstract
Robotic is a relatively young field of modern technology that exceeds traditional engineering boundaries. Control of the robots is important due to the fact that it has a usage area in many areas. In this study, modelling and control of two degrees of freedom (2-DOF) robotic arm were carried out. Lagrange-Euler method was used to obtain the dynamic equations of the robot. The system was controlled in the simulation environment. Sliding-Mode Control (SMC) and Proportional-Integral-Derivative (PID) control methods were proposed to control the 2 DOF robotic arm. The saturation function is used for the chattering problem of the sliding mode control method. Both process noise and measurement noise have been applied to control the robot in conditions close to the actual ambient conditions. The control methods applied according to the results of the simulation environment were compared and the results were examined.
Highlights
Robotic applications are widely used in engineering and technology
The saturation function is used for the chattering problem of the sliding mode control method
Mendes and Neto [12] introduce an adaptive fuzzy control that is integrated into a hybrid force/motion control system of an industrial robot to deal with a scenario of contact between the end effector of the robot and a given surface
Summary
It is well known that industrial robots are complex, dynamically coupled, high time-dependent and high nonlinear systems. These robots are commonly used in tasks such as welding, paint spraying, correct positioning systems, etc. The improved controller has relatively high stability and robustness, the controller requires a high calculation load for practical application and cannot be used for trajectory monitoring control. He et al [13] developed an adaptive controller based on artificial neural networks to address exogenous disorders and model uncertainties of an n-DOF robot manipulator. An overall evaluation of the results obtained is presented
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