Free Model Task Space Controller Based on Adaptive Gain for Robot Manipulator Using Jacobian Estimation

A Free Model Task Space Controller (FMTSC) is presented in this paper for an omnidirectional mobile manipulator. However, it is well known the difficulty to know the precsise details of the robotic system and commonly limited for the accuracy of the kinematic and dynamic model, the model based methods are not sufficient, so far. Therefore the use of available information like joints velocities and robot tip velocity allow to estimate the robot Jacobian matrix information, without any requirement of mathematical model. An adaptive Kalman filter is computed to estimate Jacobian to deal with the adaptive robot control in the task space. The control law is developed with the Jacobian estimate for Strong Tracking Kalman Filter (STKF) algortihm. The control algorithm is intended for nonlinear discrete-time system (robot) which provides adpative control gain for taks space controller, designed by Fuzzy Rules Emulated Network Adaptive Gain (FRENAG). The performance of the controller is validated with Kuka youBot mobile manipulator plataform experiments.