Flexible Robot Arm Control Using Adaptive Control ‎Structure

today, the use of different types of industrial robots is developing due to the growth of technology and the expansion of research in design and control. Industrial robots are a fundamental component of most modern automation systems. In this paper, we study the dynamic modeling and adaptive control of flexible joint robots (FJR). In this regard, the dynamic model of the robot will be extracted in state space using the Lagrange-Euler method. A new adaptive backstepping control approach is introduced to control FJR motions and improve the adaption and robustness of the nonlinear system. By using this method, variations of the model parameters will not affect the robust performance of the proposed controller. To evaluate the proposed method, MATLAB software is used to simulate a 2-joints FJR model with an adaptive backstepping controller. Based on results the proposed method controls the model property without overshoot, by considering the saturation limit of input control.