Fuzzy proportional–integral–derivative control system of electric drive downhole cutting tool based on genetic algorithm

Abstract

An electric drive downhole tubing cutting tool is the key equipment for tubing cutting in pressurized gas well workover operation. Cutting force control in radial feed movement of the cutting blade is the key to ensuring the successful cutting of tubing. In this article, the relationship model between cutting blade feed speed and cutting force is established by Matlab. Based on the mathematical model of cutting head rotation and blade feed movement, combined with the relationship between blade feed and cutting force obtained from cutting experiments. To keep the cutting force of the blade constant in the cutting process. Genetic algorithm was used to optimize the fuzzy proportional–integral–derivative control, and the automatic control scheme of the electric drive downhole tubing cutting tool was constructed. Based on Matlab/Simulink, the cutting force control simulation of the tubing cutting process is carried out. The performance of fuzzy proportional–integral–derivative control optimized by the genetic algorithm is compared with that of other standard controllers. The results show that the response speed and stability of the fuzzy proportional–integral–derivative control system are better than other algorithms. The steady-state error of the controller in the steady-cutting stage is < 5% based on the ground-cutting experiment of tubing, which meets the actual engineering needs and verifies the reliability and accuracy of the control system.