Research On The Intelligent Control System Of Electrical Impulse For Plug Removal And Making Slot Robot Used In The Well

In order to improve rate of production of jammed oil wells and low-penetrance oil wells, electrical impulse for plug removal and making slot technology has been widely promoted and applied. However there are still many limitations in specific practical application. Pipeline robot carrying electrode used to achieve the underground to carry out electrical impulse for plug removal and making slot technology overcomes many limitations of the existing technology. Intelligent control system of pipeline robot to carry out the technology of electrical impulse for plug removal and making slot is studied.For the problems of the current technology of electrical impulse for plug removal and making slot in the field specific implementation, implementation of pipeline robot carrying electrodes to carry out electrical impulse for plug removal and making slot technology has great practical value. This paper introduces the composition and working principle of electrical pulse broken instrument. For the shortcomings of only carrying out plug removal but not making slot and low degree of intelligence, the paper uses the intelligent control system of pipeline robot with the establishment of multi-sensor information fusion to solve. The paper describes the key technologies of robot and overall structure and working principle of pipeline robot. In order to control the pipeline robot, optimal design and simulation, a pipeline robot dynamic model of underground movement is established. For the control accuracy requirements of intelligent control system of pipeline robot, the paper utilizes multi-sensor information fusion to reduce information uncertainty. Multi-sensor accurate data is used as data entry of intelligent control system of pipeline robot. As the performance of control system of adaptive of pipeline robot mainly is influenced by the existence of nonlinear friction, model of adaptive robust control method based on friction compensation achieves satisfactory control effect. However, this method is poor of accuracy of parameter identification. So the paper takes advantage of neural network adaptive robust control based on dead compensation to improve, which makes use of less parameters and network to compensate and control the nonlinear part of the system. Finally, by MATLAB simulation done experiment upon on control strategy, the simulation results of PD control is compared. The performance of control system is significantly enhanced.