Abstract
Prostate cancer has one of the highest incidences of male malignant tumors worldwide. Its treatment involves the robotic implantation of radioactive seeds in the perineum, a safe and effective procedure for early, low-risk prostate cancer. In order to ensure precise positioning, the seed implantation needle is set at low terminal velocity. In this paper, the motion output position instability caused by the friction torque of the robot’s motor and rotating joint during low velocity motion was analyzed and studied. This paper also presents a compensation control method based on the LuGre friction model, which offers piecewise parameter identification with GA-PSO. First, based on an analysis of its structure and working principle, the friction torque model of the robotic system and the torque model of the driving motor are established, and the influence of friction torque on motion stability analyzed. Then, based on experimental data of the relationship between velocity and friction torque for no-friction compensation, the velocity point of the minimum torque of the rotating joint and the critical Stribeck velocity point were used for segmental parameter identification; cubic spline interpolation was used for segmental fitting. Furthermore, on the basis of the LuGre model identification method, parameter identification of the genetic algorithm-particle swarm optimization, and compensation control of the LuGre friction model, a control method is analysed and set forth. Malab2017a/Simulink simulation software was used to simulate and analyze the control method, and verify its feasibility. Finally, the cantilever prostate seed implantation robot system was tested to verify the effectiveness of the segmented identification method and the compensation control strategy. The results reveal that motion output position stability at low velocity meets the requirements of the cantilever prostate seed implantation robot, thus providing a vital reference for further research.
Highlights
Prostate cancer has one of the highest incidences of male malignant tumors worldwide [1,2]
The relationship between velocity and friction torque in the case of no-friction compensation, the the cantilever prostate seed implantation robot system was tested to verify the effectiveness of velocity point of the minimum torque of the rotating joint and the critical Stribeck velocity point the piecewise identification method using the LuGre model and the compensation control strategy were used as boundary points for segmental parameter identification; cubic spline interpolation based on the genetic algorithm—particle swarm optimization (GA-Particle swarm optimization (PSO))—for parameter identification was used for segmental fitting equation
LuGre friction model that offers piecewise parameter identification by GA-PSO, the simulation results show that the control method based on the LuGre friction model can reduce the impact of friction torque, eliminate the crawling phenomenon, alleviate the “dead zone” phenomenon in a low velocity state, and improve the low velocity stability of the robot
Summary
Prostate cancer has one of the highest incidences of male malignant tumors worldwide [1,2]. The relationship between velocity and friction torque in the case of no-friction compensation, the the cantilever prostate seed implantation robot system was tested to verify the effectiveness of velocity point of the minimum torque of the rotating joint and the critical Stribeck velocity point the piecewise identification method using the LuGre model and the compensation control strategy were used as boundary points for segmental parameter identification; cubic spline interpolation based on the genetic algorithm—particle swarm optimization (GA-PSO)—for parameter identification was used for segmental fitting equation. The control strategy of the LuGre model is of the LuGre friction model This model was found to meet the requirements of the cantilever prostate studied: the LuGre model and identification method, parameter identification based on genetic seed implantation robot for position output motion stability at low velocity, providing a vital reference algorithm-particle swarm optimization, and compensation control based on the LuGre friction for related research in the field. Open chain robot, which is composed of a moving pair and two rotating pairs
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