Neuro-fuzzy microrobotic system identification for haptic intracellular injection

Using haptic interface to control manipulator which is critical in intracellular injection has many beneficial implications. In particular, the haptic device should be able to control the microrobot in ¿m resolution, requiring an accurate model of the system. As the system has an unknown internal structure with a nonlinear behavior, a neuro-fuzzy dynamic model has been developed. Adaptive Neuro-Fuzzy Inference System (ANFIS) is employed as the system identification approach to model the non-linear dynamics. Experimental results show, the developed ANFIS model is able to predict the microrobotic system response very precise with root mean square error of 1.0224 ¿m while the microrobot manurers in cm range (10⁴ times).