| dc.description.abstract | Industrial robotic manipulator has the advantages of all-weather work, low maintenance costs, high production efficiency, has been widely used in the human factory automation production, it can improve the productivity of enterprises as well as reduce the cost of production required. However, how to precisely control the manipulator to track the desired trajectory is a crucial problem that cannot be ignored during the operation of the manipulator. In order to guarantee the accuracy and stability of the tracking process, a powerful controller is indispensable. Also, during the design process of the controller, if we can know the precise model of the robot arm, the difficulty of the controller design can be significantly reduced. Therefore, a precise model of the robotic manipulator is also an important issue to be solved. In this thesis, we will focus on both the model and the controller to overcome the tracking accuracy and stability problems of the dual-axis manipulator. Firstly, based on the nominal dynamic model of the dual-axis manipulator, we integrated various interference factors, including model uncertainties, frictions, backlash of gears, etc., to build an enhanced dynamic model of the dual-axis manipulator, which can reduce the size of unknown interferences while reducing the difficulty of controller design. Secondly, based on the developed enhanced dual-axis manipulator dynamic model, the interference factors is separated into two parts, the payload part is handled by an adaptive radial basis neural network (ARBFNN) controller, and the other interferences except the payload is estimated by the time delay estimator (TDE) to reduce the dependence on the controller parameters, and furthermore, the control signal is output by the non-singular fast terminal sliding mode controller (NFTSMC) to reduce the possible effect of external interference. Finally, we design two different simulations and demonstrate the effectiveness and superiority of the controller proposed in this paper by comparing it with various traditional control methods. | en_US |