Study on Control Strategy of Vascular Interventional Surgery Robot based on Adaptive Smith Predictor

When doctors perform cardiovascular and cerebrovascular interventional operations, X-ray radiation will greatly increase the probability of doctors suffering from cancer. Surgery through robots can protect doctors’ bodies and reduce the workload of doctors. Most of the research focus on interventional surgical robots is on traditional control algorithms. Few studies have paid attention to the delay problem of the system. Most of the vascular interventional surgery robots adopt the master-slave type, and the slave end needs to restore the action of the master end. The master-slave system cannot avoid the master-slave tracking error caused by the delay. In this paper, an adaptive Smith prediction algorithm is proposed to solve the master-slave delay and improve the tracking accuracy. This paper proves by experiments that this algorithm has a good control effect, can effectively solve the lag problem of the robot, improve the tracking performance, and ensure real-time and accuracy.