Modeling And Tracking Control Based On Equation Error Identifierfor Cardiac Signals

The research of robot assisted surgery has played an increasingly important role in the recent decade. For coronary heart disease, in the robotic-assisted off-pump Coronary Artery Bypass Graft ing(GABG) surgery, the surgery assisted robot ic tool helps the surgeon who perform remote operat ion to cancel the relat ive mot ion between the beat ing heart and robot ic too l, keeping the heart beat ing during the surgery, which will lessen post surgery co mplicat ions for patients.A characterist ic analysis o f 3D heart mot ion data through spectral too l is used to demonstrate the quasi-periodicit y o f coupling between respirat ion and heartbeat in heart mot ion, then a t ime-varying double Fourier series based equation error ident ifier algorithm is proposed to establish the heart beat mot ion model and obtain the online heart signals, which can be used the reference input of the controller. The nonlinear and quasi-periodicit y model would accurately describe the heart motion and equat ion error ident ifier algorithm would sat isfy the real time needs for the system of the change o f heart frequency and respiratory frequency.Analyzing kinemat ics and dynamics for the slave force feedback surgical robot PHANTo M. By using Lagrange equat ion, nonlinear dynamic models for robots are derived. There are two kinds o f contro l algorithms are used for time-varying heart signals and mult i jo int robot, which is a t ypical uncertain system. Simulat ion results demonstrate that the contro l algorithm meets accuracy requirements. On the other side, we creat a virtual environment to simulate the actual heart based on Quick Hapt ics too lkit of sensable techno logies, to implement tracking contro l experiment on PHANTo M by the integral sliding model contro l and nonlinear integral sliding model control algorithm, respectively.The simulat ion and experiment results indicate that the nonlinear integral sliding model contro l algorithm has higher precision than the integral sliding model control algorithms for the small range cardiac signal and mult i jo int robot.