This study presents a method of controlling robots based on fuzzy logic to eliminate the effect of uncertainties that are generated by the cutting forces in milling process. The common method to control industrial robots is based on the robot dynamic model and the differential equations of motion to compute the control values. The quantities in the differential equations of the motion of robots are complex and difficult to determine fully and accurately. The interaction forces between the cutting tool and the workpiece are the cutting forces, which are generated during the machining process. It is difficult to calculate the cutting force because it depends on many factors such as material of the machining part, depth of cut, feed rate, etc. This article presents the fuzzy rule system and the selection of the physical value domain of input and output variables of the fuzzy controller. The fuzzy rules are applied in this article to allow us to compute the driving forces based on the errors of input and output signals of the joint positions and velocities, thereby avoiding the calculation of cutting forces. This article shows the simulation results of the fuzzy controller and comparison with the results of the conventional controller when the dynamic model is assumed to be correctly determined. The achieved results are reliable and facilitate the research and application of a fuzzy controller to mechanical processing robots in general and milling machining in particular.
Inverse dynamic problem analyzing of flexible link robot with translational and rotational joints is presented in this work. The new model is developed from single flexible link manipulator with only rotational joint. The dynamic equations are built by using finite element method and Lagrange approach. The approximate force of translational joint and torque of rotational joint are found based on rigid model. The simulation results show the values of driving forces at joints of flexible robot with desire path and errors of joint variables between flexible and rigid models. Elastic displacements of end-effector are shown, respectively. There are remaining issues which need be studied further in future work because the error joints variables in algorithm to solve inverse dynamic problem of flexible with translational joint has not been mentioned yet.
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