A Real-Time State-Observer-Based Controller for a Stochastic Robotic Manipulator

Abstract

In this paper, a generalized linear feedback matrix controller is investigated for the state of n -link robot to track the desired trajectory in the presence of stochastic noise. The novel feature of the control algorithm is that it is based on $Ito^{\prime }s$ stochastic calculus for the minimization of the conditional expectation of the instantaneous tracking error energy differential with respect to the feedback matrix subject to energy constraints. The proposed control algorithm enables the adaptive features for tracking of the robotic manipulator. Additionally, the effects of feedback coefficients and parametric uncertainty on the error energies of the system are also studied using sensitivity analysis. Finally, the experimental results conducted using the “Phantom Omni™ Bundle” robot manipulator demonstrate and validate the potential application of the proposed control algorithm on a real system.