Direct adaptive neuro control for teleoperation

Abstract

This paper presents the controller design of teleoperation system. Many of uncertainty during operations through the reciprocal interaction occur at each subsystem side, master and slave. Since teleoperation applies in different places, thus control effort is hard to obtaining the certain parameters due to the fidelity of human and machine to perform some task. This research is proposed the direct adaptive neuro control. With approximation of uncertainty parametric system, radial basis function network (RBFN) is employed to approximate an uncertainty come up with input signal. This approximate signal is fed to model reference adaptive control structure with adaptive law. Disturbance is generated to incorporate with system. The result of teleoperation system is clearly explained in simulation fashion with the comparison to performance of controller. Finally we can be concluded that the purpose of design system can work well in the teleoperation applications.