Multi-Inputs and Multi-Outputs equivalent model based on data driven controller for a robotic system

Abstract This paper proposes the control of a data driven model for an experimental robotic system. The components of the robotic system are a redundant robot and a motion capture system considered them as a Multi-Inputs and Mulit-Outputs system. The Pseudo Jacobian Matrix computes the equivalent model of the robotic system taking into account the input and output signals. Besides, we design the adaptive gains for a proportional controller using an artificial neuro-fuzzy network for the robot’s end-effector control. The experimental results validate the proposed control scheme for a regulation control. We provided a Lyapunov analysis to guarantee convergence parameters of the controller.