Research On Iterative Parameters Estimation Of Non-cooperative Target Considering Flexible Robot-arm

Calculation of non- cooperative target iterative parameters in space provides core input to target’s control and stabilization, also can be of great importance to in-orbit technique. However, this technique was developed much later than that in advanced countries and the robot arm is still regarded as rigid part in the analyzing model. Under real condition, the elastic deformation of the robot-are cannot be avoided, then the complexity of the flexible dynamic equation a nd the deviation of robot-arm’s track will have a impact on the estimating properties. In order to improve the performance of parameters’ estimation, this paper promoted the dynamic controlling equation taking the flexible robot arm into consideration, which was also the estimating equation. The equations were solved and several parameters’ influence on the estimating performance was also undertaken in the paper, which was intended to summarize a better estimating strategy.In the paper, a physical model was proposed after reasonable simplification. Then the robot-arm was dispersed based on the Rayleigh Liz method and expressed in the inertial coordinate system utilizing the kinematic model. Based on the flexible dynamic theory, the dynamic controlling equations of the base, the robot arm and the non-cooperate target were derived. Combining the three equations gave the final estimating equation of the whole system. The ANSYS and ADAMS were used to simulate to get the kinematic parameters which were used to so lve the estimating equations. Finally, the problem of estimating strategy optimization was discussed.When considering the flexible property of the robot arm, the estimating accuracy is higher than that when the robot-arm is rigid. So it is meaningful to integrate the flexible property. Through analyzing the stimulating load, device error and the mass ratio of non-cooperate target and base, the estimating strategy could be gotten. There exists a best base-propulsion and a non-cooperate driving torque range, which get the smallest estimating error, and there exists a minimum that can get the iterative results fastest. The device error has a great influence on the estimating accuracy. When the mass of the target is smaller than that of the base, the estimating performance is better.