Abstract
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.
Highlights
Robots are increasingly being used in mechanical machining due to many technical and economic advantages [1–5]
Depending on the parameters of the machining process, kinematics, dynamics and the required force/torque for the robot to perform machining motion according to the machining requirements, it will estimate the physical value domain for position errors, velocity errors, and adjustment amount of the force/torque of the ith joint (i = 1, . . . , 8) of the fuzzy controller which is shown in (35)
Applying the fuzzy logic as presented, this paper proposes to set up a fuzzy controller for a robot
Summary
Robots are increasingly being used in mechanical machining due to many technical and economic advantages [1–5]. One of the solutions is controlling based on fuzzy logic to overcome the difficulty of determining cutting forces while ensuring control accuracy. Fuzzy logic is an effective tool for solving many technical problems in general [33–43], in mechanical processing and in industrial robot applications in particular. The application of fuzzy logic to control robots to eliminate the effect of cutting forces is still an open problem [62–67]. The computations based on the control law are simple linear algebra calculations that are easier and faster to perform than calculating the generalized force expression of cutting forces in the differential equations of motion of robots.
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