Robust control of robot manipulator dynamics with two stages algorithm of optimal and integral sliding mode approaches

Robot manipulators exhibit highly nonlinear dynamics influenced by uncertainties such as external disturbances and varying loads. Ensuring robust control and accurate simulation of their dynamical response is crucial for industrial applications. This article presents a novel two-stage robust optimal control approach for robotic manipulators operating under load mass uncertainties and external disturbances. In the first stage, a Linear Quadratic Regulator is applied with optimized weights to handle varying payloads of the nonlinear system in the absence of disturbances. In the second stage, a hybrid approach combining robust optimal control and Integral Sliding Mode Control is utilized to handle both payload uncertainties and external disturbances, ensuring robust stability across a wide range of operating conditions. The effectiveness of this approach is demonstrated using a two-joint SCARA robot, analyzing key variables like angular displacement, velocities, and joint torques across different payloads and bounded disturbances. The simulation results confirm the system's stable convergence, with phase portraits of sliding surfaces providing geometric insights into the stability of the nonlinear system.