Model Free Adaptive Predictive Tracking Control for Robot Manipulators with Uncertain Parameters

In this paper, a model free adaptive predictive tracking control method for the robotic manipulators with uncertain parameters is proposed. The compact form dynamic linearization method is used to transform the nonlinear robotic manipulator into a dynamic linearized data model. Then, the model free adaptive predictive tracking control algorithm is designed based on the robot manipulator data model. The proposed control method does not need accurate system model information, merely uses the input and output data of the robot manipulator which is a data-driven control method. Numerical simulations are carried out for PUMA560 robotic manipulator, and the effectiveness of the designed algorithm is verified by the simulation results.