Vahid Meigoli

Because of its ease of implementation, a linear PID controller is generally used to control robotic manipulators. Linear controllers cannot effectively cope with uncertainties and variations in the parameters; therefore, nonlinear controllers with robust performance which can cope with these are recommended. The sliding mode control (SMC) is a robust state feedback control method for nonlinear systems that, in addition having a simple design, efficiently overcomes uncertainties and disturbances in the system. It also has a very fast transient response that is desirable when controlling robotic manipulators. The most critical drawback to SMC is chattering in the control input signal. To solve this problem, in this study, SMC is used with a boundary layer (SMCBL) to eliminate the chattering and improve the performance of the system. The proposed SMCBL was compared with inverse dynamic control (IDC), a conventional nonlinear control method. The kinematic and dynamic equations of the IRB-120 robot manipulator were initially extracted completely and accurately, and then the control of the robot manipulator using SMC was evaluated. For validation, the proposed control method was implemented on a 6-DOF IRB-120 robot manipulator in the presence of uncertainties. The results were simulated, tested, and compared in the MATLAB/Simulink environment. To further validate our work, the results were tested and confirmed experimentally on an actual IRB-120 robot manipulator.