Abstract
The stick-slip is one of negative phenomena caused by friction in servo systems. It is a consequence of complicated nonlinear friction characteristics, especially the so-called Stribeck effect. Much research has been done on control algorithms suppressing the stick-slip, but no simple solution has been found. In this work, a new approach is proposed based on genetic programming. The genetic programming is a machine learning technique constructing symbolic representation of programs or expressions by evolutionary process. In this way, the servo control algorithm optimally suppressing the stick-slip is discovered. The GP training is conducted on a simulated servo system, as the experiments would last too long in real-time. The feedback for the control algorithm is based on the sensors of position, velocity and acceleration. Variants with full and reduced sensor sets are considered. Ideal and quantized position measurements are also analyzed. The results reveal that the genetic programming can successfully discover a control algorithm effectively suppressing the stick-slip. However, it is not an easy task and relatively large size of population and a big number of generations are required. Real measurement results in worse control quality. Acceleration feedback has no apparent impact on the algorithms performance, while velocity feedback is important.
Highlights
Algorithm Using GeneticFriction is a complicated nonlinear dynamic phenomenon
The results reveal that the genetic programming can successfully discover a control algorithm effectively suppressing the stick-slip
A control algorithm discovered by the Genetic programming (GP) is dedicated for a digital controller; it has to be executed with a given cycle time
Summary
Algorithm Using GeneticFriction is a complicated nonlinear dynamic phenomenon. In mechatronics and robotics, it is a force disturbing control processes of mechanical motion. Friction causes tracking errors of position control devices, commonly called as servomechanisms, or servos for short. Stick-slip effect is a specific type of such errors that emerges while a servo moves continuously with a relatively low speed. It has a form of cyclic oscillations around (or above/below) a reference trajectory (see examples in Figures 1e, 3 and 4a,b). An original paradigm and tool for design of a control algorithm for stick-slip compensated servo systems are proposed. The paradigm assumes the use of a machine learning approach to directly discover an effective control algorithm. The paradigm has been verified in simulation experiments, and its usefulness has been proven
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
